2 TRILUX LIS - Leuchten-Informationssystem 07 #8&6yDMeRj%7q2VV 8422861 TRILUX LnPlus 90-AT2L/190000-740 120G1 DMX 0 LnPlus LnPlus LnPlus LnPlus LnPlus LnPlus LnPlus 10 zum Betrieb der Lampen ist ein Vorschaltgerät notwendig. Vorschaltgerät nicht enthalten. ballast required for operation of lamps. ballast not included. do eksploatacji lamp wymagany jest statecznik. Statecznika brak w zestawie. Un ballast est nécessaire pour le fonctionnement des lampes. Ballast non compris. per il funzionamento delle lampade è necessario un reattore. reattore non compreso. Voor het gebruik van de lampen is een voorschakelapparaat nodig. Voorschakelapparaat niet inbegrepen. para la operación de las lámparas se requiere un balasto electrónico. El balasto electrónico no está incluido. 1354.00 1.0 LnPlus 90-AT2L/190000-740 120G1 DMX (TOC 8422861): LED-Flutlichtstrahler für Flächenbeleuchtung. Die Leuchte erfüllt die Anforderungen der EN 60598 und ist ausgelegt für Einwirkungen durch Wind nach EN 1991(Eurocode) mit einer Basiswindgeschwindigkeit von bis zu 30m/s (entspricht Windzone 4 in Deutschland) in der Geländekategorie 1. Montagebügel aus Aluminiumdruckguss. Der stabile Montagebügel mit 3 Bohrungen ermöglicht neben einer 2-Punkt-Befestigung auch eine zentrale 1-Punkt-Befestigung. Scheinwerferkopf durch Einpunktmontage am Montagebügel schwenkbar. Sicherung der Schwenkposition durch verzahnte Arretierungen. Scheinwerferkopf und Montagebügel sind bei Auslieferung fertig montiert. Mastmontage für Einzel- und Mehrfachanwendung mittels Zubehör möglich. In MLT-Ausführung (Multi-Lens-Technologie), bestehend aus hocheffizienten, UV- und temperaturbeständigen Linsensystemen in Vierfachanordnung. Mit asymmetrisch tief strahlender Lichtstärkeverteilung. Zur flexiblen Anpassung an kundenspezifische Beleuchtungsaufgaben stehen weitere Abstrahlcharakteristiken zur Verfügung. LED-System bestehend aus 120 MLT-LED-Modulen mit jeweils 4 LED. Bemessungslichtstrom 190000 lm, Bemessungsleistung 1.354,00 W, Leuchten-Lichtausbeute 140 lm/W. Lichtfarbe neutralweiß, ähnlichste Farbtemperatur (CCT) 4000 K, allgemeiner Farbwiedergabeindex (CRI) Ra > 70. Farborttoleranz (initial MacAdam) < 5 SDCM. Mittlere Bemessungslebensdauer L80(tq 25 °C) = 100.000 h. Die Lichtquelle ist entsprechend der Ökodesign-Anforderungen (VO (EU) 2019/2020) austauschbar. Leuchtenkörper und Abschlussscheibenträger aus Aluminiumdruckguss. Abschlussscheibe aus planem Einscheibensicherheitsglas im Trägerrahmen befestigt. Farbe Leuchtenkörper / Montagebügel: anthrazit / silbergrau, (DB 703 / RAL 9006). Leuchtengehäuse hochwetterfest pulverbeschichtet. Weitere Farbvarianten nach RAL oder DB Farbcode möglich. Maße (L x B): 983 mm x 784 mm, Höhe 342 mm. Schutzklasse (EN 61140): I, Schutzart (DIN EN 60529): IP66, Stoßfestigkeitsgrad nach IEC 62262: IK08. Windangriffsfläche fw 0,630 m². Gewicht: 38,7 kg. Mit elektronischem Betriebsgerät zum Schalten und Dimmen der Leuchte mit DMX-Steuerprotokoll. Das Betriebsgerät ist entsprechend der Ökodesign-Anforderungen (VO (EU) 2019/2020) austauschbar. Stoßspannungsfestigkeit Differential Mode / Common Mode: 10 kV / 10 kV. Das Produkt erfüllt die grundlegenden Anforderungen der anwendbaren EU-Richtlinien und des Produktsicherheitsgesetzes und trägt die CE-Kennzeichnung. LnPlus 90-AT2L/190000-740 120G1 DMX (TOC 8422861): LED floodlight for wide-area illumination. The luminaire is compliant to the requirements of EN 60598 and is designed for the effects of wind compliant to EN 1991 (Eurocode) with basic wind velocity of up to 30m/s (corresponding to wind zone 4 in Germany) in terrain category 1. Die-cast aluminium mounting bracket. The sturdy mounting bracket with 3 holes enables 2-point mounting as well as central 1-point mounting. Projector head can be swivelled on the mounting bracket by single-point mounting. Securing of swivel position by toothed locks. Projector head and mounting bracket are fully assembled on delivery. Post mounting for single and multiple arrangements is possible by means of accessories. As MLT version (Multi-Lens Technology), consisting of highly efficient UV and temperature-resistant lens systems in 4-fold configurations. With asymmetric narrow light distribution. Further beam characteristics are available for flexible adaptation to customer-specific lighting tasks. LED system consists of 120 MLT LED modules each with 4 LEDs. Luminaire luminous flux 190000 lm, connected load 1.354,00 W, Light colour neutral white, correlated colour temperature (CCT) 4000 K, general colour rendering index (CRI) Ra > 70. Colour locus tolerance (initial MacAdam) < 5 SDCM. Mean rated service life L80(tq 25 °C) = 100,000 h. The light source is replaceable according to the ecodesign requirements (VO (EU) 2019/2020). Luminaire body and cover support of die-cast aluminium. Cover of flat non-laminated safety glass fixed in frame. Colour of luminaire body / mounting bracket: anthracite / silver-grey, (DB 703 / RAL 9006). Luminaire housing highly weather resistant, powder-coated. Further colour variants possible from RAL or DB colour codes. Dimensions (L x W): 983 mm x 784 mm, height 342 mm. Safety class (EN 61140): I, protection rating (DIN EN 60529): IP66, impact resistance level in accordance with IEC 62262: IK08. Windage area fw 0,630 m². Weight: 38,7 kg. With electronic control gear for switching and dimming the luminaire with DMX control protocol. The control gear unit is replaceable in accordance with the ecodesign requirements (VO (EU) 2019/2020). The luminaire complies with the fundamental requirements of applicable EU regulations and product safety legislation and bears the CE symbol. LnPlus 90-AT2L/190000-740 120G1 DMX (TOC 8422861): Diodowy projektor iluminacyjny do oswietlania powierzchni. Oprawa spelnia wymogi normy EN 60598 i jest przeznaczona do ekspozycji na wiatr zgodnie z norma EN 1991 (Eurokod) przy podstawowej predkosci wiatru do 30 m/s (odpowiada strefie wiatru 4 w Niemczech) w terenie kategorii 1. Wspornik montazowy z cisnieniowo formowanego aluminium. Wytrzymaly wspornik montazowy z 3 otworami umozliwia montaz 2-punktowy, jak równiez centralny 1-punktowy. Glowice reflektora mozna obracac poprzez montaz jednopunktowy we wsporniku montazowym. Zabezpieczenie pozycji za pomoca zabkowanych mocowan. Glowica reflektora i wspornik montazowy sa w pelni zmontowane fabrycznie. Mozliwosc montazu na maszcie pojedynczo lub po kilka sztuk za pomoca akcesoriów. W wersji MLT (Multi Lens Technologie), obejmuje wysokowydajne systemy UV i odporne na temperatury systemy soczewkowe w konfiguracji poczwórnej. Z asymetrycznym, skupionym rozsylem swiatla. Do elastycznego dostosowania do wymogów klienta oferowane sa inne charakterystyki rozsylu swiatla. System diodowy zlozony z 120 wielosoczewkowych modulów diodowych z 4 diodami na kazdy. Strumien swietlny oprawy 190000 lm, pobór mocy 1.354,00 W, Barwa swiatla biala neutralna, temperatura barwowa 4000 K, ogólny wskaznik oddawania barw (CRI) Ra > 70. Tolerancja barwowa (initial MacAdam) < 5 SDCM. Sredni okres trwalosci znamionowej L80(tq 25 °C) = 100.000 h. Zródlo swiatla jest wymiennE zgodnie z wymogami ekoprojektu (rozporzadzenie (UE) 2019/2020). Korpus oprawy i wspornik szyby z aluminium formowanego cisnieniowo. Szyba z plaskiego, pojedynczego szkla hartowanego zamocowana w ramie nosnej. Kolor korpusu oprawy / palaka montazowego: antracytowy / srebrnoszary, (DB 703 / RAL 9006). Obudowa oprawy odporna na warunki atmosferyczne, lakierowana proszkowo. Mozliwe sa równiez inne warianty kolorystyczne wg RAL lub DB. Wymiary (dl. x szer.): 983 mm x 784 mm, wysokosc 342 mm. Klasa ochronnosci (EN 61140): I, stopien ochrony (DIN EN 60529): IP66, stopien odpornosci na uderzenia wedlug IEC 62262: IK08. Powierzchnia ekspozycji na wiatr fw 0,630 m². Masa: 38,7 kg. Z elektronicznym zasilaczem do przelaczania i sciemniania oprawy za posrednictwem protokolu sterowania DMX. Zasilacz jest wymienny zgodnie z wymogami ekoprojektu (rozporzadzenie (UE) 2019/2020). Produkt spelnia podstawowe wymogi odnosnych dyrektyw UE i niemieckiej ustawy o bezpieczenstwie produktów i posiada oznaczenie CE. LnPlus 90-AT2L/190000-740 120G1 DMX (TOC 8422861): Projecteur LED pour illumination de surfaces. Le luminaire satisfait aux exigences de la norme EN 60598, il a été conçu pour des actions du vent selon la norme EN 1991 (Eurocode), la valeur de base maximale de la vitesse de référence du vent étant de 30 m/s (correspondant à la zone de vent 4 en Allemagne) dans la catégorie de terrain I. Étrier de montage en fonte d'aluminium. L'étrier de montage stable avec 3 trous permet non seulement une fixation en 2 points mais aussi une fixation centrale en 1 point. Tête de projecteur pivotant sur l'étrier de montage grâce au montage à 1 point. Blocage de la position de pivotement par des arrêts dentés. La tête du projecteur et l'étrier de montage sont entièrement montés à la livraison. Montage sur mât possible pour une application unique ou multiple au moyen d'accessoires. En version MLT (Technologie Multi Lens), composé de systèmes de lentilles hautement efficaces, résistants aux UV et aux températures extrêmes, en montage quadruple. À répartition asymétrique intensive des intensités lumineuses. D’autres faisceaux sont disponibles pour une adaptation flexible à des tâches d’éclairage personnalisées client. Système LED composé de 120 modules LED MLT avec 4 LED chacun. Flux lumineux du luminaire 190000 lm, puissance raccordée 1.354,00 W, Teinte de lumière blanc neutre, température de couleur (CCT) 4000 K, indice général de rendu des couleurs (IRC) Ra > 70. Tolérance de localisation chromatique (initialement MacAdam) < 5 SDCM. Durée de vie assignée moyenne L80(tq 25 °C) = 100.000 h. La source lumineuse est remplaçable conformément aux exigences d'écoconception (Règlement (UE) 2019/2020). Corps du luminaire et support de la vitre de fermeture en aluminium moulé sous pression. Verre de fermeture en verre de sécurité simple plan, maintenu dans un cadre support. Couleur du corps du luminaire / de l'étrier de montage: anthracite / gris argent, (DB 703 / RAL 9006). Boîtier de luminaire très résistant aux intempéries, revêtement poudré. Possibilité d’autres variantes de couleur selon RAL ou code couleur DB. Dimensions (L x l): 983 mm x 784 mm, hauteur 342 mm. Classe électrique (EN 61140) : I, indice de protection (norme EN 60529) : IP66, degré de résistance aux chocs selon la norme CEI 62262 : IK08. Surface exposée au vent Fw 0,630 m². Poids: 38,7 kg. Avec appareillage électronique pour l'allumage et la graduation du luminaire avec protocole de commande DMX. L'appareillage est remplaçable conformément aux exigences d'écoconception (Règlement (UE) 2019/2020). Le produit répond aux exigences essentielles des directives européennes applicables et de la loi sur la sécurité des produits et porte le marquage CE. LnPlus 90-AT2L/190000-740 120G1 DMX (TOC 8422861): Proiettori a LED per l'illuminazione di superfici. L'apparecchio soddisfa i requisiti della EN 60598 ed è concepito per poter resistere all'azione del vento secondo EN 1991(Eurocode) con una velocità di base di fino a 30m/s (corrispondente alla zona di vento 4 in Germania) nella categoria di terreno 1. Staffa di montaggio in alluminio pressofuso. La robusta staffa di montaggio con 3 fori permette, oltre che un fissaggio su 2 punti, anche un fissaggio centrale su un unico punto. Testata proiettore orientabile grazie a montaggio su un solo punto della staffa di montaggio. Fissaggio della posizione di orientamento con dispositivi dentellati. La testata del proiettore e la staffa di montaggio sono già montate a finire alla consegna. Possibilità di montaggio su palo, mediante accessori appositi, per applicazione singola e multipla. In versione MLT (Multi Lens Technology), comprendente sistemi a lenti ad alta efficienza in disposizione quadrupla termoresistenti a resistenti agli UV. Con distribuzione asimmetrica concentrante del fascio luminoso. Per permettere un adattamento flessibile ad esigenze di illuminazione specifiche al cliente sono disponibili altre caratteristiche di emissione. Sistema a LED costituito da 120 moduli LED MLT con 4 LED ciascuno. Flusso luminoso apparecchio 190000 lm, potenza assorbita 1.354,00 W, Colore della luce bianco neutro, temperatura del colore (CCT) 4000 K, indice di resa cromatica generale (CRI) Ra > 70. Tolleranza cromatica (iniziale MacAdam) < 5 SDCM. Durata utile di riferimento media L80(tq 25 °C) = 100.000 h. La sorgente luminosa è intercambiabile conformemente ai requisiti previsti dal regolamento europeo Ecodesign (2019/2020). Corpo apparecchio e supporto per lastra terminale in pressofusione di alluminio.. Lastra terminale in vetro di sicurezza monolastra piatto fissata in cornice portante. Colore corpo apparecchio / staffa di montaggio: antracite / grigio argento, (DB 703 / RAL 9006). Cassa verniciata a polvere, resistente alle intemperie. Possibilità di altre varianti di colore conformi a codici RAL o DB. Dimensioni (L x P): 983 mm x 784 mm, altezza 342 mm. Classe di isolamento (EN 61140): I, grado di protezione (DIN EN 60529): IP66, grado di resistenza agli urti a norma IEC 62262: IK08. Superficie esposta al vento fw 0,630 m². Peso: 38,7 kg. Con alimentatore elettronico per la commutazione e il dimmeraggio dell'apparecchio con protocollo di controllo DMX. L'alimentatore è intercambiabile conformemente ai requisiti previsti dal regolamento europeo Ecodesign (2019/2020). L'apparecchio soddisfa i requisiti di base delle direttive Ue applicabili e della legge (tedesca) sulla sicurezza dei prodotti e reca il marchio CE. LnPlus 90-AT2L/190000-740 120G1 DMX (TOC 8422861): LED-schijnwerper voor terreinverlichting. De armatuur voldoet aan de eisen van EN 60598 en is ontworpen om bestand te zijn tegen windbelasting conform EN 1991 (Eurocode) bij een basiswindsnelheid van max. 30 m/s (stemt overeen met windzone 4 in Duitsland) in terreincategorie 1. Montagebeugel uit spuitgietaluminium. De stabiele montagebeugel met 3 boorgaten maakt naast tweepunts montage ook centrale éénpunts montage mogelijk. Schijnwerperkop aan de montagebeugel zwenkbaar door éénpunts montage. Fixering van de zwenkpositie door getande vergrendelinrichting. Schijnwerperkop en montagebeugel zijn gemonteerd bij levering. Mastmontage voor enkel- en meervoudige toepassing mogelijk door middel van toebehoren. In MLT-uitvoering (Multi-Lens-Technology), bestaande uit hoogefficiënte UV- en temperatuurbestendige lenzensystemen in viervoudige opstelling. Met diepe asymmetrische lichtverdeling. Extra stralingskarakteristieken beschikbaar voor een flexibele aanpassing aan klantspecifieke verlichtingstaken. LED-systeem bestaande uit 120 MLT-LED-modules met 4 LED’s. Armatuurlichtstroom 190000 lm, aansluitvermogen 1.354,00 W, Lichtkleur neutraal wit, kleurtemperatuur (CCT) 4000 K, algemene kleurweergave-index (CRI) Ra > 70. Kleurplaatstolerantie (initial MacAdam) < 5 SDCM. Gemiddelde opgegeven levensduur L80(tq 25 °C) = 100.000 h. De lichtbron kan vervangen worden overeenkomstig de eisen inzake ecologisch ontwerp (EU-Verordening 2019/2020). Armatuurbehuizing en afdekglasdrager uit spuitgietaluminium. Afdekglas uit vlak enkelvoudig veiligheidsglas in het dragerframe bevestigd. Kleur armatuurbehuizing/montagebeugel: antraciet / zilvergrijs, (DB 703 / RAL 9006). Armatuurbehuizing uiterst weerbestendig gepoederlakt. Andere kleuren conform RAL of kleurcode van Deutsche Bahn mogelijk. Afmetingen (L x B): 983 mm x 784 mm, hoogte 342 mm. Beschermcategorie (EN 61140): I, beschermklasse (DIN EN 60529): IP66, slagvastheid overeenkomstig IEC 62262: IK08. Windweerstandsoppervlak fw 0,630 m². Gewicht: 38,7 kg. Met elektronisch voorschakelapparaat voor het schakelen en dimmen van de armatuur met het DMX-besturingsprotocol. Het hulpapparaat kan vervangen worden overeenkomstig de eisen inzake ecologisch ontwerp (EU-Verordening 2019/2020). De armatuur voldoet aan de fundamentele eisen van de van toepassing zijnde EU-richtlijnen en de productveiligheidswet. Ze is voorzien van een CE-markering. LnPlus 90-AT2L/190000-740 120G1 DMX (TOC 8422861): Proyector LED para la iluminación bidimensional. La luminaria cumple con los requisitos de la EN 60598 y ha sido diseñada para los efectos del viento según la EN 1991(Eurocódigo) con una velocidad básica de hasta 30m/s (corresponde a una zona de viento 4 en Alemania) para la categoría de terreno 1. Estribos de montaje de aluminio colado a presión. El estribo de montaje estable con 3 perforaciones permite tanto una fijación en 2 puntos como también una fijación central en 1 punto. La cabeza de proyector puede inclinarse gracias al montaje en un punto en el estribo de montaje. Bloqueo de la posición de inclinación a través de cierres dentados. En el estado de suministro, la cabeza de proyector y el estribo de montaje están ya premontados. Los accesorios permiten un montaje en mástil para aplicaciones múltiples e individuales. En versión MLT (Multi Lens Technology), compuesta por unos sistemas de lentes altamente eficientes y resistentes a la radiación ultravioleta y a las altas temperaturas en disposición cuádruple. Con una distribución asimétrica e intensiva de las intensidades luminosas. Para una adaptación flexible a las tareas de iluminación están a su disposición otras características de iluminación. Sistema LED compuesto de 120 módulos MLT-LED con 4 LED cada uno. Flujo luminoso de las luminarias 190000 lm, potencia conectada 1.354,00 W, Color de luz color blanco neutro, temperatura del color (CCT) 4000 K, indice de reproducción cromática general (CRI) Ra > 70. Tolerancia de color (inicialmente MacAdam) < 5 SDCM. Vida útil nominal media L80(tq 25 °C) = 100.000 h. La fuente de luz puede ser sustituida acorde con los requisitos del diseño ecológico (VO (UE) 2019/2020). Cuerpo de luminaria y soporte del disco terminal fabricados en aluminio colado a presión. Disco terminal de cristal plano de seguridad fijado en el marco de soporte. Color del cuerpo de luminaria/estribo de montaje: antracit / gris plata, (DB 703 / RAL 9006). Cuerpo de luminaria altamente resistente a la intemperie, lacado en polvo. Son posibles otras variantes de color según RAL o código de color DB. Dimensiones (L x A): 983 mm x 784 mm, altura 342 mm. Clase de protección (EN 61140): I, grado de protección (DIN EN 60529): IP66, grado de la resistencia al impacto según IEC 62262: IK08. Superficie atacada por el viento fw 0,630 m². Peso de: 38,7 kg. Con equipamiento eléctrico para la conmutación y regulación de la luminaria con protocolo de control DMX.. El equipamiento eléctrico puede sustituirse según los requisitos del diseño ecológico (VO (EU) 2019/2020). El producto cumple con los requisitos básicos de las directrices europeas aplicables y de la ley para la seguridad de aparatos y productos y lleva el marcado CE. 1 1354.00 190000.00 4000K 70 983 784 342 760 555 0 0 0 0 EULUM TX464414.LDT ![CDATA[TRILUX 3 0 144 2.5 73 2.5 c223012 LnPlus 90-AT2L/190000-740 120G1 DMX TX464414 21.04.2023 - Lux 983 784 342 760 555 0 0 0 0 100 99.9921798706055 1 0 1 1 1 x LED 190000 4000K 70 1354 .208813100597931 .30643409063358 .387067303950757 .483819147861786 .554484753592967 .642733781788535 .713601891509363 .768588693503557 .815560090268799 .853040107475339 0 2.5 5 7.5 10 12.5 15 17.5 20 22.5 25 27.5 30 32.5 35 37.5 40 42.5 45 47.5 50 52.5 55 57.5 60 62.5 65 67.5 70 72.5 75 77.5 80 82.5 85 87.5 90 92.5 95 97.5 100 102.5 105 107.5 110 112.5 115 117.5 120 122.5 125 127.5 130 132.5 135 137.5 140 142.5 145 147.5 150 152.5 155 157.5 160 162.5 165 167.5 170 172.5 175 177.5 180 182.5 185 187.5 190 192.5 195 197.5 200 202.5 205 207.5 210 212.5 215 217.5 220 222.5 225 227.5 230 232.5 235 237.5 240 242.5 245 247.5 250 252.5 255 257.5 260 262.5 265 267.5 270 272.5 275 277.5 280 282.5 285 287.5 290 292.5 295 297.5 300 302.5 305 307.5 310 312.5 315 317.5 320 322.5 325 327.5 330 332.5 335 337.5 340 342.5 345 347.5 350 352.5 355 357.5 0 2.5 5 7.5 10 12.5 15 17.5 20 22.5 25 27.5 30 32.5 35 37.5 40 42.5 45 47.5 50 52.5 55 57.5 60 62.5 65 67.5 70 72.5 75 77.5 80 82.5 85 87.5 90 92.5 95 97.5 100 102.5 105 107.5 110 112.5 115 117.5 120 122.5 125 127.5 130 132.5 135 137.5 140 142.5 145 147.5 150 152.5 155 157.5 160 162.5 165 167.5 170 172.5 175 177.5 180 148.3 151.29 151.51 150.92 148.2 150.13 147.42 150.59 150.43 149.12 148.65 150.89 147.08 146.61 142.25 140.69 136.66 130.15 124.23 115.49 106.88 99.11 93.7 87.72 83.71 85.02 84.08 78.85 67.54 51.2 34.29 10.78 2.47 .47 .18 .08 .01 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 151.47 153.17 152.52 150.93 153.95 149.23 152.92 153.9 152.33 152.21 153.24 152.11 152.13 149.91 147.31 143.31 137.42 133.27 121.94 114.15 105.87 98.78 94.2 91.58 92.36 95.74 91.6 78.13 61.42 37.78 11.56 2.91 .47 .18 .08 .01 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 151.68 152.67 153.88 154.67 154.81 151.59 155.66 156.53 158.64 159.1 156.65 159.86 157.15 156.42 153.49 152.48 148.26 141.45 131.39 122.06 115.19 107.12 102.02 99.47 99.87 102.59 100.86 87.41 66.87 40.98 12.49 3.12 .53 .18 .08 .01 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 151.72 153.09 154.1 154.14 154.15 156.06 158.51 160.42 162.32 161.02 164.33 166.88 165.65 165.86 163.97 161.8 156.27 151.49 142.45 132.62 124.46 117.97 110.44 106.58 107.09 110.3 107.92 95.84 70.66 43.52 14.08 3.8 .51 .18 .08 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 151.77 151.74 155.84 156.01 155.96 159.63 160.66 163.31 164.12 168.73 170.12 171.96 172.52 172.19 171.51 172.16 167.09 158.97 151.53 142.33 135.01 126.63 120.06 114.57 113.32 116.63 111.69 99.49 73.39 45.53 15.43 3.95 .55 .18 .08 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 151.92 153.22 156.96 155.09 159.25 161.59 161.9 167.97 169.27 172.48 175.12 179.45 179.7 182.72 184.1 182 178.86 172.71 162.26 154.02 145.15 138.99 133.18 127.22 125.12 123.36 116.16 101.99 76.49 47.84 17.36 4.76 .57 .18 .08 .01 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 152.19 155.37 158.99 158.12 162.63 166.56 165.92 171.39 175.04 180.9 182.81 189.12 189.07 192.21 194 193.98 192.02 184.05 176.66 165.81 157.09 149.34 145.26 142.13 136.56 131.56 121.21 102.92 78.62 50.27 20.26 5.64 .67 .19 .08 .01 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 152.3 156.54 159.91 160.01 164.18 168.4 172.05 177.74 180.12 185.07 190.86 194.01 199.73 201.53 204.23 204.42 202.45 200.01 190.34 179.84 172.06 164.95 160.33 153.73 146.86 141.52 126.41 108.78 83.35 55.08 23.78 6.75 .76 .19 .08 .01 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 151.82 158.81 160.19 161.44 167.03 169.48 175.83 180.45 186.64 192.08 198.76 203.46 207.66 212.4 214.96 219.93 217.31 216.09 207.47 196.74 185.47 181.18 175.73 164.07 157.95 146.71 131.21 112.83 86.93 58.77 29.64 7.86 .89 .19 .07 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 152.97 156.79 160.97 164.39 169.38 174.21 179.97 186.97 193.89 196.48 206.29 212.78 219.97 226.57 230.48 236.86 239.52 238.54 233.31 224.79 209.51 195.74 187.53 178.73 165.39 152.74 136.25 115.76 93.7 66.62 34.55 9.38 1.27 .19 .08 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 153.14 159.79 160.57 168.05 171.89 178.97 183.77 187.71 197.66 206.99 215.15 221.78 233.56 241.39 249.95 261.75 268.7 266.62 264.6 248.77 235.67 215.57 199.36 189.24 173 161.91 143.78 122.5 100.53 72.84 42.66 12.75 1.56 .2 .07 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 153.51 161.6 160.11 170.86 172.27 182.57 186.31 196.53 205.01 215.1 223.35 236.44 245.76 261.93 275.63 289.04 294.86 303.17 293.14 278.75 255.44 228.5 208.62 196.4 182.03 167.37 150.9 132.66 111 86.11 55.67 19.58 2.44 .23 .07 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 152.92 161.04 161.57 171.56 175.78 188.64 193.15 202.24 212 221.04 237.19 249.48 268.3 284.04 303.52 321.7 331.36 336.28 323.33 298.32 271.49 241.29 221.21 201.07 193.71 181.39 166.27 151.94 133.04 104.51 67.98 28.27 3.47 .3 .08 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 153.51 161.14 165.43 174.68 179.85 187.95 198.4 208.05 218.72 233.68 249.21 267.28 290.54 315.12 335.2 356.48 362.96 356.16 342.68 318.5 285.53 254.2 233.83 219.41 209.04 198.54 189.56 180.28 160.88 126.97 85.07 37.13 5.15 .34 .08 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 155.15 161.9 165.75 173.79 184.14 191.8 201.6 214.82 227.73 244.79 266.1 289.64 318.18 345.72 364.62 380.27 378.86 368.84 354.15 331.18 300.36 271.78 249.78 235.98 227.22 225.56 226.36 213.36 188.37 149.31 97.83 47.1 7.17 .38 .09 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 156.18 163.94 168.49 173.72 185.79 196.06 205.34 220.48 235.94 258.68 284.52 315.76 346.56 372.09 393.8 396.24 394.06 381.58 366.78 349.89 319.84 295.86 275.03 262.17 258.68 260.37 265.37 251.15 211.84 158.68 106.12 55.11 10.22 .42 .1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 156.98 162.99 170.8 176 187.87 201.54 209.97 227.06 243.75 273.13 303.61 341.95 377.91 402.12 407.96 406.27 399.14 394.48 381.29 361.08 341.49 317.62 305.04 294.47 296.05 304.1 297.07 273.67 221.67 164.87 107.31 58.09 11.67 .43 .09 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 158.33 163.43 171.5 181.35 188.26 202.88 215.53 234.41 256.11 291.49 326.58 368.2 399.96 411.4 416.66 412.78 407.78 400 392.93 378.95 361.56 345.85 335.65 335.05 335.21 335.95 326.04 282.73 220.4 156.4 100.3 55.71 11.53 .42 .09 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 158.46 164.72 172.45 182.53 192.93 204.69 222.25 242.07 271.8 308.11 349.6 385.67 415.54 425.74 422.89 418.95 413.35 408.05 403.96 390.91 384.23 369.22 368.92 368.69 375.76 375.69 347.43 286.3 214.99 144.34 89.39 49.93 10.83 .39 .07 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 158.09 163.86 173.06 185.77 196.24 209.38 227.94 250.97 285.08 326.91 374.07 413.24 424.76 428.88 426.97 421.51 418.92 417.46 418.14 413.52 403.59 398.49 401.33 405.89 414.96 402.22 360.15 285.31 199.3 130.73 78.61 42.29 9.33 .36 .07 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 158.43 163.92 172.75 188.74 198.98 213.09 230.06 262.45 301.5 353.84 397.23 428.18 429.96 431.85 430.39 424.08 424.83 430.73 431.86 431.05 427.37 426.56 431.29 438.52 446.83 425.04 367.78 279.48 188.24 119.14 70.06 36.33 8.86 .34 .06 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 159.26 162.5 173.89 188.56 200.42 216.95 237.3 272.04 314.1 371.61 412.73 433.77 436.25 433.13 427.85 427.68 432.18 443.26 448.42 445.27 450.77 454.83 469.9 479.19 477.53 450.9 370.23 269.92 180.58 111.23 63.98 33.19 8.75 .32 .06 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 159.11 164.11 175.55 189.6 203.81 220.9 243.34 284.42 330.72 384.73 424.6 438.35 440.56 433.78 435.8 432.05 442.65 452.92 462.26 467.34 474.63 492.04 507.88 520.55 509.15 466.07 372.58 262.75 174.06 107.15 62.15 33.07 8.3 .27 .05 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 159.44 165.23 175.58 189.86 205.97 222.91 251.92 295.97 345.82 400.61 433.57 443.61 441.46 435.91 435.84 437.7 453 466.94 475.47 491.91 508.93 526.72 546.62 556.32 537.23 475.98 370.94 256.6 170.13 103.18 62.57 32.46 8.63 .27 .05 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 159.62 164.57 178.67 190.9 208.71 227.84 260.34 305.05 360.9 418.05 438.62 446.62 440.99 437.84 444.29 446.89 454.92 482.11 494.65 522.23 540.43 565.88 586.26 591.49 563.03 485 363.63 255.73 162.78 101.08 60.52 31.93 7.82 .24 .05 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 159.35 167.07 179.59 192.34 209.92 230.72 266.82 313.31 375.02 426.06 443.11 449.69 444.71 436.68 443.22 453.74 469.62 487.35 517.63 547.64 577.72 608.28 626.01 621.61 576.54 487.02 361.17 246.44 160.94 97.5 60.28 31.78 6.54 .23 .05 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 158.24 168.74 182.45 192.73 212.54 236.06 273.06 322.04 384.8 431.33 446.41 443.48 445.42 450.53 447.83 462.24 478.45 497.43 542.48 581.9 620.65 646.27 652.59 639.84 588.47 482.93 357.87 242.86 156.03 94.43 58.08 28.08 4.94 .23 .04 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 158.65 169.13 182.57 194.59 212.1 240.25 280.18 333.91 399.29 436.18 447.24 449.02 447.3 448.39 452.76 471.95 484.66 525.95 570.61 615.87 653.18 678.18 679.35 656.78 589.34 474.89 348.19 233.17 143.45 87.1 51.46 22.63 3.71 .22 .03 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 159.42 170.9 183.31 196.26 213.81 244.88 283.54 342.92 407.34 436.38 449.79 448.17 450.39 450.72 458.82 475.29 501.82 545.67 598.19 652.23 684.19 702.87 696.03 660.3 586.65 465.5 337.09 219.15 130.23 76.72 43.12 19.23 2.53 .18 .03 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 159.63 170.74 182.78 198.28 215.41 248.35 289.13 353.01 413.59 439.82 448.12 449.54 451.51 453.66 465.22 488.28 518.63 566.48 628.46 678.05 709.69 719.52 709.22 669.78 580.15 456.89 319.66 196.42 112.69 66.92 36.88 13.91 2.02 .16 .04 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 159.39 170.67 183.18 199.41 221.1 249.32 297.72 362.89 416.23 443.54 452.69 453.67 449.65 458.06 469.75 497.93 530.64 584.67 657.67 707.44 723.12 728.99 715.58 670.12 575.36 437.99 294.05 173.74 95.1 59.2 31.81 12.66 1.81 .14 .03 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 158.93 170.9 182.55 200.51 221.11 247.86 302.25 361.9 422.62 445.5 453.79 453.33 456.68 462.13 480.5 504.02 543.59 610.7 673.58 720.6 740.46 740.4 719.24 666.19 560.31 416.67 269.42 147.47 83.36 54.03 29.87 12.46 1.71 .14 .04 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 158.7 172.1 183.55 200.04 223.69 248.1 306.03 368.4 426.31 443.9 451.49 450.56 453.04 469.82 488.7 513.37 559.42 625.13 700.66 736.77 749.78 746.99 723.46 657.72 542.11 396.26 238.17 127.36 75.1 52.23 29.07 12.26 1.53 .13 .04 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 159.38 171.24 184.56 204 221.53 251.53 307.09 372.11 428.04 447.06 452.14 455.45 456.72 467.71 489.84 521.67 570.61 645.77 710.62 744.34 756.28 748.9 717.62 656.62 530.94 371.7 216.97 115.11 74.29 51.89 28.44 12.49 1.45 .13 .04 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 159.9 171.07 185.94 202.36 221.35 253.59 309.44 373.85 430.48 446.49 454.31 451.91 456.08 465.14 492.79 530.87 579.7 654.07 724.44 754.43 764.16 752.54 722.95 642.82 519.62 356.53 200.88 104.23 71.59 51.82 27.82 12.33 1.32 .15 .04 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 159.24 170.35 186.79 201.29 222.01 252.17 309.05 382.58 430.98 445.97 456.08 452.87 456.04 472.5 496.62 530.4 584.81 664.37 723.49 759.88 760.26 758.29 717.85 642.89 508.11 339.49 191.65 103.95 72.72 52.42 27.65 12.22 1.37 .13 .04 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 158.66 170.42 188.01 204.09 222.1 256.58 308.39 383.34 427.74 450.17 452.98 455.81 455.76 467.88 492.47 532.55 587.52 677.88 730.67 759.34 769 746.11 716.82 638.48 507.75 339.88 186.12 102.64 72.8 52.08 28.19 12.4 1.47 .12 .04 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 159.24 170.35 186.79 201.29 222.01 252.17 309.05 382.58 430.98 445.97 456.08 452.87 456.04 472.5 496.62 530.4 584.81 664.37 723.49 759.88 760.26 758.29 717.85 642.89 508.11 339.49 191.65 103.95 72.72 52.42 27.65 12.22 1.37 .13 .04 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 159.9 171.07 185.94 202.36 221.35 253.59 309.44 373.85 430.48 446.49 454.31 451.91 456.08 465.14 492.79 530.87 579.7 654.07 724.44 754.43 764.16 752.54 722.95 642.82 519.62 356.53 200.88 104.23 71.59 51.82 27.82 12.33 1.32 .15 .04 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 159.38 171.24 184.56 204 221.53 251.53 307.09 372.11 428.04 447.06 452.14 455.45 456.72 467.71 489.84 521.67 570.61 645.77 710.62 744.34 756.28 748.9 717.62 656.62 530.94 371.7 216.97 115.11 74.29 51.89 28.44 12.49 1.45 .13 .04 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 158.7 172.1 183.55 200.04 223.69 248.1 306.03 368.4 426.31 443.9 451.49 450.56 453.04 469.82 488.7 513.37 559.42 625.13 700.66 736.77 749.78 746.99 723.46 657.72 542.11 396.26 238.17 127.36 75.1 52.23 29.07 12.26 1.53 .13 .04 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 158.93 170.9 182.55 200.51 221.11 247.86 302.25 361.9 422.62 445.5 453.79 453.33 456.68 462.13 480.5 504.02 543.59 610.7 673.58 720.6 740.46 740.4 719.24 666.19 560.31 416.67 269.42 147.47 83.36 54.03 29.87 12.46 1.71 .14 .04 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 159.39 170.67 183.18 199.41 221.1 249.32 297.72 362.89 416.23 443.54 452.69 453.67 449.65 458.06 469.75 497.93 530.64 584.67 657.67 707.44 723.12 728.99 715.58 670.12 575.36 437.99 294.05 173.74 95.1 59.2 31.81 12.66 1.81 .14 .03 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 159.63 170.74 182.78 198.28 215.41 248.35 289.13 353.01 413.59 439.82 448.12 449.54 451.51 453.66 465.22 488.28 518.63 566.48 628.46 678.05 709.69 719.52 709.22 669.78 580.15 456.89 319.66 196.42 112.69 66.92 36.88 13.91 2.02 .16 .04 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 159.42 170.9 183.31 196.26 213.81 244.88 283.54 342.92 407.34 436.38 449.79 448.17 450.39 450.72 458.82 475.29 501.82 545.67 598.19 652.23 684.19 702.87 696.03 660.3 586.65 465.5 337.09 219.15 130.23 76.72 43.12 19.23 2.53 .18 .03 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 158.65 169.13 182.57 194.59 212.1 240.25 280.18 333.91 399.29 436.18 447.24 449.02 447.3 448.39 452.76 471.95 484.66 525.95 570.61 615.87 653.18 678.18 679.35 656.78 589.34 474.89 348.19 233.17 143.45 87.1 51.46 22.63 3.71 .22 .03 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 158.24 168.74 182.45 192.73 212.54 236.06 273.06 322.04 384.8 431.33 446.41 443.48 445.42 450.53 447.83 462.24 478.45 497.43 542.48 581.9 620.65 646.27 652.59 639.84 588.47 482.93 357.87 242.86 156.03 94.43 58.08 28.08 4.94 .23 .04 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 159.35 167.07 179.59 192.34 209.92 230.72 266.82 313.31 375.02 426.06 443.11 449.69 444.71 436.68 443.22 453.74 469.62 487.35 517.63 547.64 577.72 608.28 626.01 621.61 576.54 487.02 361.17 246.44 160.94 97.5 60.28 31.78 6.54 .23 .05 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 159.62 164.57 178.67 190.9 208.71 227.84 260.34 305.05 360.9 418.05 438.62 446.62 440.99 437.84 444.29 446.89 454.92 482.11 494.65 522.23 540.43 565.88 586.26 591.49 563.03 485 363.63 255.73 162.78 101.08 60.52 31.93 7.82 .24 .05 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 159.44 165.23 175.58 189.86 205.97 222.91 251.92 295.97 345.82 400.61 433.57 443.61 441.46 435.91 435.84 437.7 453 466.94 475.47 491.91 508.93 526.72 546.62 556.32 537.23 475.98 370.94 256.6 170.13 103.18 62.57 32.46 8.63 .27 .05 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 159.11 164.11 175.55 189.6 203.81 220.9 243.34 284.42 330.72 384.73 424.6 438.35 440.56 433.78 435.8 432.05 442.65 452.92 462.26 467.34 474.63 492.04 507.88 520.55 509.15 466.07 372.58 262.75 174.06 107.15 62.15 33.07 8.3 .27 .05 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 159.26 162.5 173.89 188.56 200.42 216.95 237.3 272.04 314.1 371.61 412.73 433.77 436.25 433.13 427.85 427.68 432.18 443.26 448.42 445.27 450.77 454.83 469.9 479.19 477.53 450.9 370.23 269.92 180.58 111.23 63.98 33.19 8.75 .32 .06 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 158.43 163.92 172.75 188.74 198.98 213.09 230.06 262.45 301.5 353.84 397.23 428.18 429.96 431.85 430.39 424.08 424.83 430.73 431.86 431.05 427.37 426.56 431.29 438.52 446.83 425.04 367.78 279.48 188.24 119.14 70.06 36.33 8.86 .34 .06 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 158.09 163.86 173.06 185.77 196.24 209.38 227.94 250.97 285.08 326.91 374.07 413.24 424.76 428.88 426.97 421.51 418.92 417.46 418.14 413.52 403.59 398.49 401.33 405.89 414.96 402.22 360.15 285.31 199.3 130.73 78.61 42.29 9.33 .36 .07 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 158.46 164.72 172.45 182.53 192.93 204.69 222.25 242.07 271.8 308.11 349.6 385.67 415.54 425.74 422.89 418.95 413.35 408.05 403.96 390.91 384.23 369.22 368.92 368.69 375.76 375.69 347.43 286.3 214.99 144.34 89.39 49.93 10.83 .39 .07 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 158.33 163.43 171.5 181.35 188.26 202.88 215.53 234.41 256.11 291.49 326.58 368.2 399.96 411.4 416.66 412.78 407.78 400 392.93 378.95 361.56 345.85 335.65 335.05 335.21 335.95 326.04 282.73 220.4 156.4 100.3 55.71 11.53 .42 .09 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 156.98 162.99 170.8 176 187.87 201.54 209.97 227.06 243.75 273.13 303.61 341.95 377.91 402.12 407.96 406.27 399.14 394.48 381.29 361.08 341.49 317.62 305.04 294.47 296.05 304.1 297.07 273.67 221.67 164.87 107.31 58.09 11.67 .43 .09 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 156.18 163.94 168.49 173.72 185.79 196.06 205.34 220.48 235.94 258.68 284.52 315.76 346.56 372.09 393.8 396.24 394.06 381.58 366.78 349.89 319.84 295.86 275.03 262.17 258.68 260.37 265.37 251.15 211.84 158.68 106.12 55.11 10.22 .42 .1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 155.15 161.9 165.75 173.79 184.14 191.8 201.6 214.82 227.73 244.79 266.1 289.64 318.18 345.72 364.62 380.27 378.86 368.84 354.15 331.18 300.36 271.78 249.78 235.98 227.22 225.56 226.36 213.36 188.37 149.31 97.83 47.1 7.17 .38 .09 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 153.51 161.14 165.43 174.68 179.85 187.95 198.4 208.05 218.72 233.68 249.21 267.28 290.54 315.12 335.2 356.48 362.96 356.16 342.68 318.5 285.53 254.2 233.83 219.41 209.04 198.54 189.56 180.28 160.88 126.97 85.07 37.13 5.15 .34 .08 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 152.92 161.04 161.57 171.56 175.78 188.64 193.15 202.24 212 221.04 237.19 249.48 268.3 284.04 303.52 321.7 331.36 336.28 323.33 298.32 271.49 241.29 221.21 201.07 193.71 181.39 166.27 151.94 133.04 104.51 67.98 28.27 3.47 .3 .08 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 153.51 161.6 160.11 170.86 172.27 182.57 186.31 196.53 205.01 215.1 223.35 236.44 245.76 261.93 275.63 289.04 294.86 303.17 293.14 278.75 255.44 228.5 208.62 196.4 182.03 167.37 150.9 132.66 111 86.11 55.67 19.58 2.44 .23 .07 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 153.14 159.79 160.57 168.05 171.89 178.97 183.77 187.71 197.66 206.99 215.15 221.78 233.56 241.39 249.95 261.75 268.7 266.62 264.6 248.77 235.67 215.57 199.36 189.24 173 161.91 143.78 122.5 100.53 72.84 42.66 12.75 1.56 .2 .07 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 152.97 156.79 160.97 164.39 169.38 174.21 179.97 186.97 193.89 196.48 206.29 212.78 219.97 226.57 230.48 236.86 239.52 238.54 233.31 224.79 209.51 195.74 187.53 178.73 165.39 152.74 136.25 115.76 93.7 66.62 34.55 9.38 1.27 .19 .08 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 151.82 158.81 160.19 161.44 167.03 169.48 175.83 180.45 186.64 192.08 198.76 203.46 207.66 212.4 214.96 219.93 217.31 216.09 207.47 196.74 185.47 181.18 175.73 164.07 157.95 146.71 131.21 112.83 86.93 58.77 29.64 7.86 .89 .19 .07 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 152.3 156.54 159.91 160.01 164.18 168.4 172.05 177.74 180.12 185.07 190.86 194.01 199.73 201.53 204.23 204.42 202.45 200.01 190.34 179.84 172.06 164.95 160.33 153.73 146.86 141.52 126.41 108.78 83.35 55.08 23.78 6.75 .76 .19 .08 .01 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 152.19 155.37 158.99 158.12 162.63 166.56 165.92 171.39 175.04 180.9 182.81 189.12 189.07 192.21 194 193.98 192.02 184.05 176.66 165.81 157.09 149.34 145.26 142.13 136.56 131.56 121.21 102.92 78.62 50.27 20.26 5.64 .67 .19 .08 .01 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 151.92 153.22 156.96 155.09 159.25 161.59 161.9 167.97 169.27 172.48 175.12 179.45 179.7 182.72 184.1 182 178.86 172.71 162.26 154.02 145.15 138.99 133.18 127.22 125.12 123.36 116.16 101.99 76.49 47.84 17.36 4.76 .57 .18 .08 .01 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 151.77 151.74 155.84 156.01 155.96 159.63 160.66 163.31 164.12 168.73 170.12 171.96 172.52 172.19 171.51 172.16 167.09 158.97 151.53 142.33 135.01 126.63 120.06 114.57 113.32 116.63 111.69 99.49 73.39 45.53 15.43 3.95 .55 .18 .08 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 151.72 153.09 154.1 154.14 154.15 156.06 158.51 160.42 162.32 161.02 164.33 166.88 165.65 165.86 163.97 161.8 156.27 151.49 142.45 132.62 124.46 117.97 110.44 106.58 107.09 110.3 107.92 95.84 70.66 43.52 14.08 3.8 .51 .18 .08 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 151.68 152.67 153.88 154.67 154.81 151.59 155.66 156.53 158.64 159.1 156.65 159.86 157.15 156.42 153.49 152.48 148.26 141.45 131.39 122.06 115.19 107.12 102.02 99.47 99.87 102.59 100.86 87.41 66.87 40.98 12.49 3.12 .53 .18 .08 .01 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 151.47 153.17 152.52 150.93 153.95 149.23 152.92 153.9 152.33 152.21 153.24 152.11 152.13 149.91 147.31 143.31 137.42 133.27 121.94 114.15 105.87 98.78 94.2 91.58 92.36 95.74 91.6 78.13 61.42 37.78 11.56 2.91 .47 .18 .08 .01 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 151.29 151.51 150.92 148.2 150.13 147.42 150.59 150.43 149.12 148.65 150.89 147.08 146.61 142.25 140.69 136.66 130.15 124.23 115.49 106.88 99.11 93.7 87.72 83.71 85.02 84.08 78.85 67.54 51.2 34.29 10.78 2.47 .47 .18 .08 .01 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 150.33 148.35 149.24 149.38 149 147.64 148.41 145.79 145.59 143.81 145.52 142.04 141.7 139.88 134.39 127.99 123.95 116.21 107.52 99.99 91.38 85.39 79.86 77.99 75.9 70.16 64.41 53.64 41.05 29.36 9.85 3.52 .46 .18 .07 .01 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 150.44 148.99 147.24 146.62 146.45 145.47 143.74 142.29 143.79 143.05 140.57 140.67 137.61 133.92 129.56 127.71 119.38 113.18 102.9 92.34 82.31 75.29 69.8 67.66 64.04 56.98 50.7 43.49 35.34 26.05 9.13 3.81 .46 .17 .09 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 149.8 148.83 144.26 146.79 146.66 143.54 142.04 141.22 142.07 141.08 138.71 139.25 136.22 130.14 128.34 121.31 114.63 106.32 94.37 80.09 69.55 62.33 59.08 58.45 52.67 46.65 42.84 36.66 30.01 22.92 8.75 4.85 .47 .16 .08 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 148.89 149.14 143.73 145.88 145.42 140.26 139.84 138.78 137.99 140.55 138.57 137.02 134.97 131.98 126.19 118.26 110.01 97.4 82.44 70.03 61.54 57.68 53.22 51.14 48.51 42.38 37.1 32.25 26.76 20.45 8.7 3.27 .5 .15 .07 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 147.71 148.1 143.31 144.72 143.24 140.03 137.47 139.31 139.68 142.27 138.76 138.15 132.71 131.54 125.1 112.9 101.66 86.21 75.95 65.45 60.01 54.77 51.48 49.04 42.26 39.06 34.1 28.68 24.92 18.44 8.69 2.98 .51 .14 .07 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 147.91 147.47 143.48 141.84 139.94 141.06 138.07 139.47 139.59 140.02 140.73 137.58 133.9 127.64 121.52 109.61 93.41 83.54 72.87 65.85 60.98 56.43 51.06 46.7 40.92 37.19 32.27 28.92 22.41 18.34 9.45 2.99 .56 .13 .06 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 147.05 147.55 144.15 139.27 138.29 139.66 138.35 139.38 143.55 140.81 141.32 139.14 134.03 127.14 116.46 105.03 91.02 80.69 73.46 68.77 62.3 56.1 51.59 47.26 42.14 36.99 32.11 27.43 22.7 17.73 10.29 3.83 .61 .13 .05 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 146.38 147.61 142.77 139.79 135.79 138.24 140.8 137.95 145.27 145.26 140.73 138.77 132.73 123.2 111.39 100.61 90.09 80.36 77.53 70.8 64.86 59.36 54.76 49.34 44.06 40.14 35.11 30.64 24.62 18.81 11.41 5.05 .86 .14 .05 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 145.78 147.46 141.85 139.04 136.77 135.91 140.17 140.01 146.76 148.77 144.22 138.91 131.73 122.77 107.74 98.95 91.3 86.04 79.51 74.51 66.84 61.75 56.48 52.17 47.36 44.39 39.18 33.33 26.5 21.36 12.92 5.78 1 .13 .05 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 144.94 145.98 141.06 136.47 137.9 141.12 142.11 143 146.08 145.7 146.69 138.83 129.86 119.3 109.16 102.04 94.4 87.61 81.35 74.63 71.36 65.01 59.43 56 50.95 48.07 41.26 36.85 29.49 22.22 14.31 6.94 1.24 .12 .04 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 145.31 144.17 140.99 136.31 137.4 139.31 142.04 146.66 148.41 147.96 145.62 138.72 126.99 117.86 108.66 104.26 97.37 91.62 83.95 79.63 75.37 68.84 65.62 59.69 55.53 51.31 44.84 37.54 30.25 23.44 15.52 7.9 1.5 .13 .05 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 145.4 142.28 140.91 136.84 137.33 139.91 143.09 147.92 149.57 149.48 147.97 137.67 125.39 120.82 111.85 107.57 99.76 93.71 88.94 84.63 77.36 75.41 68.68 65.4 60.02 55.54 48.88 38.83 31.6 24.52 16.41 8.54 2.14 .15 .04 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 144.89 139.88 139.83 134.27 137.12 140.29 144.2 150.13 149.73 151.43 144.4 134.16 127.55 123.42 116.86 111.09 103.71 99.03 92.28 87.13 83.85 80.6 73.72 69.52 63.22 57.52 49.89 41.74 33.34 25.22 17.07 8.74 2.37 .15 .04 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 145.09 139.48 138.32 134.46 136.93 140.03 145.11 150.37 153.31 146.61 143.83 135.94 128.79 126.4 121.24 114.26 107.81 100.9 96.69 93.58 87.62 83.31 79.06 72.26 68.87 58.96 51.18 43.43 33.02 25.25 17.29 8.51 2.49 .15 .05 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 144.54 140.64 137.96 133.92 139.26 141.49 147.63 150.42 150.44 148.95 141.92 136.79 132.88 128.89 124.73 119.18 111.27 108.26 101.13 98.08 92.27 87.45 81.4 77.76 69.8 60.36 53.03 42.35 33.41 24.51 17.43 9.4 2.63 .17 .05 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 144.38 141.01 137.43 135.24 139.51 142.35 147.43 150.71 151.77 149.34 144.15 141.9 135.74 134.14 129.09 121.58 116.1 114.15 107.13 102.53 97.21 91.08 83.43 79.49 70.74 60.93 51.15 42.24 33.17 24.41 17.59 9.86 2.66 .17 .05 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 143.6 139.58 137.8 135.77 141.48 143.05 148.04 151.31 153.55 148.47 144.92 141.8 139.25 134.44 131.81 126.31 120.89 115.57 112.89 108 99.98 94.27 88.23 82.69 70.63 62.08 51.04 41.65 33.37 24.85 17.69 9.77 2.76 .18 .05 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 144.24 139.21 137.52 136.18 141.43 143.51 148.91 149.33 154.06 149.31 146.55 144.13 142.39 140.95 135.28 128.95 126.72 123.44 115.84 110.84 103.99 96.57 93.18 83.69 74.57 62.36 51.19 41.5 33.53 25.12 17.8 9.51 2.63 .19 .06 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 144.23 139.66 138.09 140.65 140.76 143.93 149.91 152.8 152.91 149.46 147.15 147.47 146.58 143.69 138.92 135.36 131.48 128.24 121.22 114.28 107.75 101.3 95.31 86.79 75.16 64.65 53.93 44.57 33.92 25.08 17.63 9.56 2.76 .22 .05 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 144.1 139.34 138.23 139.02 141.82 145.74 150.21 155.78 152.78 150.42 150.9 152.52 149.99 146.09 142.66 138.43 138.38 132.77 125.55 118.79 111.53 107.77 99.62 89.19 77.36 67.89 54.98 45.56 35.18 25.13 16.35 8.77 2.68 .2 .06 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 145.04 139.68 139.07 138.39 141.39 146.36 150.76 155.65 154.26 149.78 153.72 154.12 152.05 150.61 147.27 144.07 142.93 139.74 130.25 123.93 115.12 111.63 103.15 92.45 78.89 69.24 56.84 45.93 35.35 25.87 15.92 9.05 2.43 .22 .07 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 145.86 139.48 138.42 138.4 142.17 148.66 152.55 155.12 154.71 150.95 155.32 156.82 157.95 155.54 150.56 149.5 146.98 142.28 133.39 125.57 121.45 114.46 106.75 94.11 83.87 72.22 59.2 47.12 36.27 24.99 15.61 8.64 2.21 .2 .08 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 145.74 139.12 137.07 137.69 143.13 147.54 154.72 156.63 154.34 156.59 157.33 159.87 158.71 155.13 157.13 156.73 151.33 145.56 139.24 129.27 124.9 120.07 110.21 98.25 86.58 73.29 60.98 49.02 36.56 25.41 14.79 7.83 1.98 .21 .08 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 145.76 138.3 136.92 140.36 143.51 147.01 156.1 158.23 154.01 159.19 162.44 160.89 161.29 159.73 161.13 160.26 153.74 149.3 142.09 134.25 129.15 126.77 111.17 104.19 88.53 76.29 62.85 50.8 36.36 24.17 14.19 6.97 1.68 .22 .08 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 145.58 138.58 136.54 140.36 145.6 149.45 156.51 156.15 156.14 160.85 163.44 161.98 163.94 162.46 164.08 163.05 157.14 152.99 145.11 139.15 134.18 126.35 115.66 103.9 90.87 77.54 64.11 49.41 35.63 24.07 13.87 7.18 1.46 .2 .08 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 145.16 138.04 136.2 139.85 145.32 151.39 155.96 157.14 156.9 161.17 165.91 163.55 165.01 165.15 168.39 165.02 160.43 155.7 149.64 141.05 138.77 130.86 118.67 109.3 93.41 77.67 63.98 49.73 35.77 22.94 13.06 6.03 1.27 .2 .08 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 144.91 139.02 137.86 139.1 146.3 152.36 157 155.89 159.6 164.5 167.24 169.93 167.82 169.87 172.02 168.82 162.86 157.3 152.61 143.51 143.26 132.77 121.11 108.75 94.87 77.5 62.5 46.75 34.39 21.72 12.57 5.97 1.14 .19 .08 .01 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 145.22 138.21 137.64 138.34 145.18 152.86 156.94 155.99 159.82 165.2 168.96 167.25 171.24 172.91 173.55 170.03 165.33 159.84 153.36 148.72 141.07 136.84 121.19 107.71 94.72 77.55 60.65 46.19 32.09 20.19 11.54 5.54 1.14 .17 .08 .01 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 144.86 137.45 137.41 140.16 145.97 152.61 157.54 156.86 161.85 168.81 169.45 170.12 173.12 175.42 175.67 173.21 167.08 161.87 158.5 150.31 146.58 136.28 122.84 110.01 92.25 74.8 59.72 44.58 31.21 19.05 11.37 4.84 .93 .18 .09 .01 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 144.43 137.54 137.29 141.6 145.74 154.59 158.25 156.09 161.73 169.07 170.23 172.06 172.12 178.39 176.35 173.66 168.64 165.76 158.56 152.33 149.44 137.79 123.26 109.61 93 74.29 57.73 42.14 29.6 18.29 10.93 4.69 .84 .19 .09 .01 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 144.9 137.02 137.24 141.38 145.84 154.95 159.16 157.63 164.23 169.48 172.46 174.18 177 180.9 179.03 174.32 169.18 164.6 158.44 154.45 147.97 136.15 124.43 108.67 91.54 72.02 55.16 41.85 28.78 17.84 10.52 4.27 .85 .21 .09 .01 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 144.97 137.32 137.01 140.68 145.54 154.62 158.08 159.79 164.67 173.05 175.33 177.34 177.62 181.89 180.05 174.81 171.67 167.67 160.24 154.27 149.73 137.16 124.01 108.79 92.14 70.57 53.93 40.35 27.75 18.16 10.39 4.31 .79 .22 .1 .01 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 145.26 137.38 137.93 140.79 145.3 153.19 159.45 158.62 163.84 172.5 175.82 175.47 178.51 183.82 178.77 176.57 172.41 166.13 161.54 154.46 149.34 138.38 123.35 108.94 87.89 70.53 53.02 39.7 27.69 17.52 10.44 4.2 .77 .22 .1 .01 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 144.87 137.8 138.23 142.18 146.22 154.01 160 158.55 164.72 170.63 174.46 174.29 177.03 182.99 180.92 177.49 172.69 166.59 162.63 155.73 149.97 138.14 125.26 107.28 88.46 67.67 52.9 38.37 27.76 17.19 10.52 4.29 .79 .23 .11 .01 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 144.54 135.97 138.76 141.38 146.29 156.06 158.68 158.48 165.69 171.58 174.76 176.97 181.25 182.19 179.04 174.99 172.27 168.63 160.95 158.28 149.99 138.5 124.09 106.5 90.52 68.87 52.8 39.26 27.75 17.65 11.67 4.09 .78 .22 .11 .01 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 144.9 135.58 139.4 140.53 148.03 152.24 158.97 158.63 167.9 173.1 175.99 180.6 175.31 183.36 180.8 177.57 172.72 164.58 161.83 150.09 148.48 139.84 122.98 108 87.3 67.43 53.17 40.62 27.48 18.24 11.71 4.51 .7 .22 .11 .01 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 144.54 135.97 138.76 141.38 146.29 156.06 158.68 158.48 165.69 171.58 174.76 176.97 181.25 182.19 179.04 174.99 172.27 168.63 160.95 158.28 149.99 138.5 124.09 106.5 90.52 68.87 52.8 39.26 27.75 17.65 11.67 4.09 .78 .22 .11 .01 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 144.87 137.8 138.23 142.18 146.22 154.01 160 158.55 164.72 170.63 174.46 174.29 177.03 182.99 180.92 177.49 172.69 166.59 162.63 155.73 149.97 138.14 125.26 107.28 88.46 67.67 52.9 38.37 27.76 17.19 10.52 4.29 .79 .23 .11 .01 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 145.26 137.38 137.93 140.79 145.3 153.19 159.45 158.62 163.84 172.5 175.82 175.47 178.51 183.82 178.77 176.57 172.41 166.13 161.54 154.46 149.34 138.38 123.35 108.94 87.89 70.53 53.02 39.7 27.69 17.52 10.44 4.2 .77 .22 .1 .01 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 144.97 137.32 137.01 140.68 145.54 154.62 158.08 159.79 164.67 173.05 175.33 177.34 177.62 181.89 180.05 174.81 171.67 167.67 160.24 154.27 149.73 137.16 124.01 108.79 92.14 70.57 53.93 40.35 27.75 18.16 10.39 4.31 .79 .22 .1 .01 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 144.9 137.02 137.24 141.38 145.84 154.95 159.16 157.63 164.23 169.48 172.46 174.18 177 180.9 179.03 174.32 169.18 164.6 158.44 154.45 147.97 136.15 124.43 108.67 91.54 72.02 55.16 41.85 28.78 17.84 10.52 4.27 .85 .21 .09 .01 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 144.43 137.54 137.29 141.6 145.74 154.59 158.25 156.09 161.73 169.07 170.23 172.06 172.12 178.39 176.35 173.66 168.64 165.76 158.56 152.33 149.44 137.79 123.26 109.61 93 74.29 57.73 42.14 29.6 18.29 10.93 4.69 .84 .19 .09 .01 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 144.86 137.45 137.41 140.16 145.97 152.61 157.54 156.86 161.85 168.81 169.45 170.12 173.12 175.42 175.67 173.21 167.08 161.87 158.5 150.31 146.58 136.28 122.84 110.01 92.25 74.8 59.72 44.58 31.21 19.05 11.37 4.84 .93 .18 .09 .01 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 145.22 138.21 137.64 138.34 145.18 152.86 156.94 155.99 159.82 165.2 168.96 167.25 171.24 172.91 173.55 170.03 165.33 159.84 153.36 148.72 141.07 136.84 121.19 107.71 94.72 77.55 60.65 46.19 32.09 20.19 11.54 5.54 1.14 .17 .08 .01 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 144.91 139.02 137.86 139.1 146.3 152.36 157 155.89 159.6 164.5 167.24 169.93 167.82 169.87 172.02 168.82 162.86 157.3 152.61 143.51 143.26 132.77 121.11 108.75 94.87 77.5 62.5 46.75 34.39 21.72 12.57 5.97 1.14 .19 .08 .01 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 145.16 138.04 136.2 139.85 145.32 151.39 155.96 157.14 156.9 161.17 165.91 163.55 165.01 165.15 168.39 165.02 160.43 155.7 149.64 141.05 138.77 130.86 118.67 109.3 93.41 77.67 63.98 49.73 35.77 22.94 13.06 6.03 1.27 .2 .08 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 145.58 138.58 136.54 140.36 145.6 149.45 156.51 156.15 156.14 160.85 163.44 161.98 163.94 162.46 164.08 163.05 157.14 152.99 145.11 139.15 134.18 126.35 115.66 103.9 90.87 77.54 64.11 49.41 35.63 24.07 13.87 7.18 1.46 .2 .08 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 145.76 138.3 136.92 140.36 143.51 147.01 156.1 158.23 154.01 159.19 162.44 160.89 161.29 159.73 161.13 160.26 153.74 149.3 142.09 134.25 129.15 126.77 111.17 104.19 88.53 76.29 62.85 50.8 36.36 24.17 14.19 6.97 1.68 .22 .08 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 145.74 139.12 137.07 137.69 143.13 147.54 154.72 156.63 154.34 156.59 157.33 159.87 158.71 155.13 157.13 156.73 151.33 145.56 139.24 129.27 124.9 120.07 110.21 98.25 86.58 73.29 60.98 49.02 36.56 25.41 14.79 7.83 1.98 .21 .08 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 145.86 139.48 138.42 138.4 142.17 148.66 152.55 155.12 154.71 150.95 155.32 156.82 157.95 155.54 150.56 149.5 146.98 142.28 133.39 125.57 121.45 114.46 106.75 94.11 83.87 72.22 59.2 47.12 36.27 24.99 15.61 8.64 2.21 .2 .08 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 145.04 139.68 139.07 138.39 141.39 146.36 150.76 155.65 154.26 149.78 153.72 154.12 152.05 150.61 147.27 144.07 142.93 139.74 130.25 123.93 115.12 111.63 103.15 92.45 78.89 69.24 56.84 45.93 35.35 25.87 15.92 9.05 2.43 .22 .07 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 144.1 139.34 138.23 139.02 141.82 145.74 150.21 155.78 152.78 150.42 150.9 152.52 149.99 146.09 142.66 138.43 138.38 132.77 125.55 118.79 111.53 107.77 99.62 89.19 77.36 67.89 54.98 45.56 35.18 25.13 16.35 8.77 2.68 .2 .06 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 144.23 139.66 138.09 140.65 140.76 143.93 149.91 152.8 152.91 149.46 147.15 147.47 146.58 143.69 138.92 135.36 131.48 128.24 121.22 114.28 107.75 101.3 95.31 86.79 75.16 64.65 53.93 44.57 33.92 25.08 17.63 9.56 2.76 .22 .05 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 144.24 139.21 137.52 136.18 141.43 143.51 148.91 149.33 154.06 149.31 146.55 144.13 142.39 140.95 135.28 128.95 126.72 123.44 115.84 110.84 103.99 96.57 93.18 83.69 74.57 62.36 51.19 41.5 33.53 25.12 17.8 9.51 2.63 .19 .06 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 143.6 139.58 137.8 135.77 141.48 143.05 148.04 151.31 153.55 148.47 144.92 141.8 139.25 134.44 131.81 126.31 120.89 115.57 112.89 108 99.98 94.27 88.23 82.69 70.63 62.08 51.04 41.65 33.37 24.85 17.69 9.77 2.76 .18 .05 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 144.38 141.01 137.43 135.24 139.51 142.35 147.43 150.71 151.77 149.34 144.15 141.9 135.74 134.14 129.09 121.58 116.1 114.15 107.13 102.53 97.21 91.08 83.43 79.49 70.74 60.93 51.15 42.24 33.17 24.41 17.59 9.86 2.66 .17 .05 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 144.54 140.64 137.96 133.92 139.26 141.49 147.63 150.42 150.44 148.95 141.92 136.79 132.88 128.89 124.73 119.18 111.27 108.26 101.13 98.08 92.27 87.45 81.4 77.76 69.8 60.36 53.03 42.35 33.41 24.51 17.43 9.4 2.63 .17 .05 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 145.09 139.48 138.32 134.46 136.93 140.03 145.11 150.37 153.31 146.61 143.83 135.94 128.79 126.4 121.24 114.26 107.81 100.9 96.69 93.58 87.62 83.31 79.06 72.26 68.87 58.96 51.18 43.43 33.02 25.25 17.29 8.51 2.49 .15 .05 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 144.89 139.88 139.83 134.27 137.12 140.29 144.2 150.13 149.73 151.43 144.4 134.16 127.55 123.42 116.86 111.09 103.71 99.03 92.28 87.13 83.85 80.6 73.72 69.52 63.22 57.52 49.89 41.74 33.34 25.22 17.07 8.74 2.37 .15 .04 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 145.4 142.28 140.91 136.84 137.33 139.91 143.09 147.92 149.57 149.48 147.97 137.67 125.39 120.82 111.85 107.57 99.76 93.71 88.94 84.63 77.36 75.41 68.68 65.4 60.02 55.54 48.88 38.83 31.6 24.52 16.41 8.54 2.14 .15 .04 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 145.31 144.17 140.99 136.31 137.4 139.31 142.04 146.66 148.41 147.96 145.62 138.72 126.99 117.86 108.66 104.26 97.37 91.62 83.95 79.63 75.37 68.84 65.62 59.69 55.53 51.31 44.84 37.54 30.25 23.44 15.52 7.9 1.5 .13 .05 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 144.94 145.98 141.06 136.47 137.9 141.12 142.11 143 146.08 145.7 146.69 138.83 129.86 119.3 109.16 102.04 94.4 87.61 81.35 74.63 71.36 65.01 59.43 56 50.95 48.07 41.26 36.85 29.49 22.22 14.31 6.94 1.24 .12 .04 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 145.78 147.46 141.85 139.04 136.77 135.91 140.17 140.01 146.76 148.77 144.22 138.91 131.73 122.77 107.74 98.95 91.3 86.04 79.51 74.51 66.84 61.75 56.48 52.17 47.36 44.39 39.18 33.33 26.5 21.36 12.92 5.78 1 .13 .05 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 146.38 147.61 142.77 139.79 135.79 138.24 140.8 137.95 145.27 145.26 140.73 138.77 132.73 123.2 111.39 100.61 90.09 80.36 77.53 70.8 64.86 59.36 54.76 49.34 44.06 40.14 35.11 30.64 24.62 18.81 11.41 5.05 .86 .14 .05 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 147.05 147.55 144.15 139.27 138.29 139.66 138.35 139.38 143.55 140.81 141.32 139.14 134.03 127.14 116.46 105.03 91.02 80.69 73.46 68.77 62.3 56.1 51.59 47.26 42.14 36.99 32.11 27.43 22.7 17.73 10.29 3.83 .61 .13 .05 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 147.91 147.47 143.48 141.84 139.94 141.06 138.07 139.47 139.59 140.02 140.73 137.58 133.9 127.64 121.52 109.61 93.41 83.54 72.87 65.85 60.98 56.43 51.06 46.7 40.92 37.19 32.27 28.92 22.41 18.34 9.45 2.99 .56 .13 .06 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 147.71 148.1 143.31 144.72 143.24 140.03 137.47 139.31 139.68 142.27 138.76 138.15 132.71 131.54 125.1 112.9 101.66 86.21 75.95 65.45 60.01 54.77 51.48 49.04 42.26 39.06 34.1 28.68 24.92 18.44 8.69 2.98 .51 .14 .07 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 148.89 149.14 143.73 145.88 145.42 140.26 139.84 138.78 137.99 140.55 138.57 137.02 134.97 131.98 126.19 118.26 110.01 97.4 82.44 70.03 61.54 57.68 53.22 51.14 48.51 42.38 37.1 32.25 26.76 20.45 8.7 3.27 .5 .15 .07 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 149.8 148.83 144.26 146.79 146.66 143.54 142.04 141.22 142.07 141.08 138.71 139.25 136.22 130.14 128.34 121.31 114.63 106.32 94.37 80.09 69.55 62.33 59.08 58.45 52.67 46.65 42.84 36.66 30.01 22.92 8.75 4.85 .47 .16 .08 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 150.44 148.99 147.24 146.62 146.45 145.47 143.74 142.29 143.79 143.05 140.57 140.67 137.61 133.92 129.56 127.71 119.38 113.18 102.9 92.34 82.31 75.29 69.8 67.66 64.04 56.98 50.7 43.49 35.34 26.05 9.13 3.81 .46 .17 .09 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 148.3 150.33 148.35 149.24 149.38 149 147.64 148.41 145.79 145.59 143.81 145.52 142.04 141.7 139.88 134.39 127.99 123.95 116.21 107.52 99.99 91.38 85.39 79.86 77.99 75.9 70.16 64.41 53.64 41.05 29.36 9.85 3.52 .46 .18 .07 .01 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 ]] JPEG MS_Lumena_Plus_90.jpg /9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAUDBAQEAwUEBAQFBQUGBwwIBwcHBw8LCwkMEQ8S EhEPERETFhwXExQaFRERGCEYGh0dHx8fExciJCIeJBweHx7/2wBDAQUFBQcGBw4ICA4eFBEU Hh4eHh4eHh4eHh4eHh4eHh4eHh4eHh4eHh4eHh4eHh4eHh4eHh4eHh4eHh4eHh4eHh7/wAAR CAQABAADASIAAhEBAxEB/8QAHQABAAICAwEBAAAAAAAAAAAAAAcIAQYEBQkCA//EAFwQAAED AwIDAgQODAsGBgMAAwABAgMEBREGBwgSIRMxFCJBURUWFxgyU2Fxc5GSk7GyCSMkN0JSVWJy gcHRJTM0NTZUVmN0gqEmQ0RklOEnKDiDoqNFRnWEZfD/xAAUAQEAAAAAAAAAAAAAAAAAAAAA /8QAFBEBAAAAAAAAAAAAAAAAAAAAAP/aAAwDAQACEQMRAD8AuWAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAADDnNa1 XOcjUTvVVNQv+5WjrLWLRV93jjm7sNXIG4A6zT19tV7pEqLZWR1DPccmTswAOo1HqWzafpVq LrXRQMTzuTPxHU6e3G0hfqjsLbdopJO7DlwBtoCKiplFRU86AAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAqoiZVcIfHbQ+2x/KQD7B1OqL3TWTT 1bd5HxuZSxLIqcydcET6V4ldAXWpdS1lwjpZ0XHL3gTa5cIq+YjzfrWNx0ZoZ95tqN7ZJWN8 ZM9FU2fT+rtPX1nPbLlBMmM+yRCN+LnD9qJnsc1yJUR9y/nASPoa61F50xRXCoVqSzMa52E8 6EeVG4l2i30t+jmo3wKo5ufp16G47UyRN0LbEdLFnsm/hp06EN1ytTivs7u1Y5q9p1RyKgFl AdZeNQWi0QrLX10MLU78vQjLV/ETt1YWvZ6LxzTt7mIneBMAIq2S3iotynTupaeOCKJVw7n7 8EpNlicuGyMVfccgH2dVqnUNr03aZbldaqOngjbnL3YydqVl3IfV7n71x6MSR3oPa5kStjRe j2r5wOxuu/V8vEsnpP0xcZYGO5UndDzMf7qKcvS+/wBLR1rKDW1ir7c+RcNqZI+SP41Jcpqe waF0z2cUcNFb6WLKr0ToiFbdV+inEVqZ9ptcTqPTdG5eWvan8Ynl6Ab3pjdDVOvNzEo9K0/Z 6cgRWzTyMyj3J5lJ4ZnkTm78dSt3CnWv0nf7rtxUN7RYZ3OhmXvc1vlLItVHJlO4CFeLDWV5 09oxLfYIpFr6yRsaPansWuXCmp7YcNdlrNOR3HVtdcKm5VSc71SdcJnqWFvNhtN3cx1xo46h WKit5k7jnxsjghRrURkbEx7iIBTbVFvuOwG6tsmtdwqKiy1y+NHLIrsZXCFtK+7rTaUkvbW9 ojaVJ0aid/TJVXfq5N3V3rtOkdPtWdlA/FS9vVGua7JbSgoImWKC3TRo6NsDYntXy4TCgVG0 Do+8b56+vN31TUV1JZ6KpVkULXqzmavuGz7u8PVq09peo1Ho6vr6att0azqjp1w5GlkLNZrb Z2SMttJHTpIuXIxO9SMuJzXlDpfbytt8j2rXXKN1PDGi5XKp0A/LhV17Vaz2+j8PVX1lE1GS r51JiTqmSDeDnR9bprbxKyuY5k1xRJFavkJyAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAA6/UVJUV1kqqSlk7OaVitY7OMKV/qdnNyH1M72akw178 tTt16IWQAFUNf7SbgUWi7pWVl/WaKKBXPjSZV5k94p1TaW1NWXSRlBaq2R/PjmjjVf8AU9bL jRU1wo5KSriSWCRMPavcqHVWXSGnbOqrbrZBCqrlcNAoNt3spvDcJI5aC4VVvaqouJJHNJa3 W0RrjTuzs0eo7rHVN7SNq4kVVzkt21rW9zUT3kIb4vPvVy/4iP6wEdaG2O1LXabo6pupauNk jUcjW1KoiIqGo23b67Wnfqgsr7tNNPUI/lldKqq3p5y1W03L6RLZn2puPiIZrEROLK0dc+zA 0Xczhv3MrqietoNTSSxKqu7N1Q5envFfNX7Sa+sk7lrbXVVit73MjVyHqifjUUtPURrHNCx7 V70VqAUB4XtvdZ3mOobb6ia2cqrzI9VYWP2+2t1zZNTwV9yvvhFKx2Xs7ZVyTHaLDarVI+Sg o44HPXLlanedkBhrcMRq9ehWKC7Uu3fEZfK28osFHeJESKaTo3onnLLV9U2jpJ6qVMRQxq9y +4hUbca0XriG1k630FLJb7RbHryVqJ/GAd7fa7U2+ms1s9sSai0nSyfbpVy1ZVavkXyopYHT NhseitNto6KKOlpKWPL5FTGfOqqV90dcN0NrKB+nYdIS3OjifiOq5kTmRO45F5l3h3RkZaH2 6p01aZV5aiRFyj2gfexjZNS753fVFGxfAaWSSn50To5fOWaRMdxq22WirZofTcdqt7G8yoiz yInWR/lU2kAQLxPbpTWehbo/TL0nvVxXsFSPq6PPl6dxu2/G5FBt7o6prZXtWse3khjz1VVy mSAeG2j0/U3qo3I17eop7pVvXsIpv91heigS/wANW1kGi9PJdrkztb1cESaokk6ua5e/qTGa nHuLo58rImXmBXvXDUz3mxVdfS0ttkuM0qNpo2do5/mb5wOo19qm16Q09UXq6TpHHE1eVM4V V8hWbavTN23p3Kl17qdsiWamk+44HdGqrV6Lg6LX+so94t3I9OzXTwDTFFIrZn58WXC5Qstp bVW3mm7LDarZdKWGngYjcN8qoneBv1PDFTwthhY2ONiYa1qYREPs6vT98tl7hfPbKxlTGner fIdoAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AACGeL5vNtTMnXHhEf1iZiG+LtVTaqZPJ4RH9YDddo28ug7YiLn7U3v94hutz67Gz5x/vCZN p0RdCWvK4xEz6CG65UXixs+P7wCyYAAAAD5ljZLE6KRqOY9MORe5UOLbLXb7ZGsdBRw0zV70 jYiZOYAPmSOORMSMRye6hmNjY28rGo1PMhkAAABHe8O0entzII4r5PUxpGmG9k7BHbOErRDY 0Yl7vjWp3NbPhELEACAbdwraMoq6KrZfL658Tkc1HT9OhNVfZKWs01LYZXv8Hlg7BzkXxuXG DtABXh/CVoRauWojul3gWV3M7s5cZUz60zROFT0ev/X/AJgsMANL2p25tW3lsloLVV1lTHKq Kq1D+ZUwboAAAAAAAAAAB1OqdR2jTVtfcLxWMpYGJlXOUjJ3Eftskjm+jdOuFwi57wJjBEVB xDbcVVdFSpe6drpHYRckrUFXT19HFWUkrZYJWo5j07lQD9wAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABo+7evK jQ1qhrYLLPdFkk5FZGuFT3SNXcRdwRMpoOvX/OBYIFeJOJWWKpSlm0ZWMnVMpGr+qn7LxE3B FwuhK/5YFgQV9XiKuP8AYKvx5+cxHxFXJ3foKvTzeOBYMFfPXF3LlVfSFX9Fx7MyvETcfFxo KvXP54FggV+XiJuSP5fSFX9345hnEVcXNVfSHXpj88CwQK+rxFXFHIi6Dr8L5ecLxFXBEVfS JXr/AJwLBAr7HxFXJ3foKvT/ADhOIq5K5UTQVeuPzwLBAr6nEVcMddB16L5ucN4ibkrFd6Qq /p+eBYIFfE4jLiuP9g6/r+eZXiKuKP5V0HX+/wA4FggV8dxF3BGqqaDr1/zmW8RVyVqqugq9 F83OBYIFfPXF3HCKugq/r+efXriblz8vpCr/AH+cCwIK+rxFXJFd/sFcPF/PMpxE3BW83pEr /lgWBBX13EXcEblNB16/5yZNC6gk1JYorlLQyUTnoi9k9eqAd8ARBv8Ab32PbS3rErmVVye3 7XA13X3wJdke1jcq5rfNlSHOLd7XbSzL2kar4RF5fzinmsuJfcO9Vjn0NyfRw82WsxnBpupt 3dfaitvofd7y+emyi8itx1TuA9K9qHsboW2JzsX7U3y+4QzX8qcWNmcr24+2dylR7ZvhuVbq KKkpL9JHDFjkbydx1Tt0dau1NHqJ11etyjzyy8vdkD1eWaFFx2rPjHbw+2s+M8vXb97o5VfT DIufzAu/W6OP6QyL/kA9Qu3h9tZ8Y7eH21nxnl4m/O6LUz6YJMfoGWb87nqqr6Y3p/kA9Qu3 h9tZ8Y7eH21nxnmJFvdu1LMkMd7me9UyiJH3ocifeDeSmhWSW61LGJ3qsYHpn28PtrPjHbw+ 2s+M8zId395Z4kkiulS9i+VIz4qt5d4aZiLUXeojR3cqxgem3bw+2s+MdvD7az4zzOZu7vO6 Jr23OpVrk6L2XecSo3u3ZpJFiqL5LE5O9HMA9PO3h9tZ8Y7eH21nxnmTQ7y7v1bHSUl4nlai 9VazJ+qbubz83S51WfggPTHt4fbWfGO3h9tZ8Z5nru3vRnPolVdP7oJu7vOvT0TqvmgPTDt4 fbWfGO3h9tZ8Z5n+q3vQ1f5yquv90fLt3t5msc510qUa1Mqqx9wHpl28PtrPjHbw+2s+M8xK Xe3dqok7Gnvssj/xUZ1OW3dvehMolyqvmgPTDt4fbWfGFnix0lZn3zzObu5vPlcXKqyv90Z9 VzejGfRKq+aA9L2Tx8vjSsz75nt4fbWfGeZ6bu70KuEuVV80F3c3oRcLcqr5oD0w7eH21nxm HTx48WVmffPM9N295+qpcqr3ftR+dVvLvFSRdrUXeeJnndHgCzfH5WPj0Tb44arkRznczWu9 l75VzZbZLUW51vnrLPLTtZC/kd2j8Ka7qzXetddy09FeLhJcHc2ImInepJe1+md9dJ2vtNL0 FZSwzqj+jM5Ajndjby8bcakW1XSWPwhmFR0bs4PQnhgrXz7UWtaiqSVWQtRFc7Kp0KO7t6Q3 dutUt/1ha6ud7vZSKzHcdfpncDdTTttS32erqaemTuZ2ecAeoSTx8y5lj5fJ1P0a5rky1UVP cPMap3k3hgj5p7vPGzzujwWT4Kt09T6wdWUGoat1YrH4Y/GMIBacGGKqouUwZAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAOPW0NJWsRlXTxztRcoj25OEmn7KnMq2qlRE7vEQ7U4l3rIaO2VNTK9EbHGqqv6gKf7yau oLfxK22209HS+Cu7Njkx07+pbKnstknp2zMtdI5rmorV5E69Dy/3D1PNX7u1F4kkV/g1cvKu fI1x6T7KXtuoNtbRdEdzLLCmeoHfJYLNnC2ql5cfiIZdYLMjelrpVVO7xEOzAHVegFn7vQql xj8RO8yywWblTNrpUX9BDtAB1XoDaOq+hVLnPTxEHoBZ05sWql9zxEO1AHVLYLNyp/BVKq+b kQz6XrJ+S6X5CHaADq/QCz8yYtdLjz8iHyyw2lObNqpE83iIdsAOqXT9m5c+hVJzfoIfXoBZ kauLZS+9yIdmAOq9L9m5M+hVJzebkQy7T9mwn8FUqr+gh2gA6z0vWT8l0vzaGHWCzJ3WulX/ ACIdoAOqWwWfqnoVS9O7xEPpLBZsZ9C6XP6CHZgDqksFo6ZtVL17/EQy3T9mwqLaqVPN4iHa ADqk0/ZuTPoVSc3m5EOwpYIqeJI4YmxNT8FqdD9QBp+72tKLRGi6271UiNkbEvYp+M480rvU 33dHcWR7ZJqqorJ8xMVVXkYq9yFhuP8A1w6aup9KU8uPB380iIveinxwB7ex1dbUayq2N5qV 3ZxtcnfkCO9O7dUelN+7Tpe6wtqUc6J0sb0ymHeQspxR6B0ZadspKu26foKWdJo0R8cSIuFU jDXzlXjQpst5vHiTBOfF196mTpj7oj+kDm7Xba6FqtF26oqdM22WVY2uVzoUVVXBEtbovSvr n7XbG2OiSik5+aDs05F/UWF2m/oJbOmftTfoK2bta+tOh+IeivlWqVDafn5mNXuUCxM21+3M EbnzaZtMbM+ydE1EQijc/U2w+g2yQz2O11NYnsGxQtemf1EDbib97gbmXSSz6ThqIqR7lRsL G5dj3zEXD1fafQtdrTWVY+NY8OWnmVebqBpu6mqm7kXVlNpbSFNRUrXIjXUlOqKvv4OBpGzW 3SV/Z6faWSKGX2DUjyvxFzuFDQll09tytwnoI3zukWRHvai+L3p3lYd+LlNrziAksdPA1II6 lGxtagE88Ke2dmq4KvVd1tkE8ckrmUrJGZTs19iuDduJ3TGmrdsxfKqnslJDKyNOV8cSIqdT Zo71p/a/bGgluMkdO1lO1EYq4V78dyEKavve5u89qqrVaLTU2ew1fi9rKzLZEz5FAljYvSWm anbK0VE9jopJJKZjlc+JFVeho/Fhpmw0VntK0lno6dzpVRysjRDrtOaT36sFlhtFv1JEyCBi Mj+0dyJ3HV6y2z3t1lSw0d71LFIyFVVi9jjAE7aF0jpOXRlndNZLc5zqViqqxplVwVJ4nrNp um37oaOppm0lodM1KnwdnVG48x0F+15u/pXVNLox1+RZY3JDC7k8mcIbHrDZbd/UFwS8XOu8 MqZGNdzJF7gG1cPOnbDLu26m05bX1+mOR6zS1kPVH+TBaf0k6Sz/AEet3zKFKadu/e3WnZ5q R60VHG9GqroEy73cne6a1HxLahs8d1t9xc6CRcJiDzAW59JOk/7P2/5lAmiNJJ/+vW75lCq/ hHFH/X5PmB4RxR/1+T5gC1C6J0mvfp+3/MoRTxRaUo6LbKql07p2jSbld2jo4sOa3HkwRb4R xR/1+T5g/KrTicrKWSlqqp0kMjeV7Vp+9AI80JZ9OPrtJpp+mq6u7vYvh8UsS8iOz5S89r0X phbfTrNp23o9Ymq/7UnfjqU203oLfPT1zmuNqiWKpldzK5YEXC+4bV4RxR/16T5gC1CaJ0kn dp63/MoPSTpLu9L1v+ZQprq3XXEZpispKO5XNzJaz+KzDjJsEFZxQzU8czLg9WyNRyYg84Fq k0TpJO7T1v8AmUC6J0kvfp+3/MoU/wBW6r4k9L2ea7XO5OZTQpl6rDg63b3cbiH11QyVtjua yQsdyqrYc9QLpJonSSd2nrf8yhVPi60/baTcK1QVtr8B026Nvay0kXXmydJrHXm/2j1oPTHq FlCytcrWPkhwjcHBv2o9T6voo6PUu5tonpVw7CxIiovvgRjeblpXSO9VDdbCx9VZaORkiNnZ 7Lp1yhYiLjCs8UaRxW5kbGphGtj6IhC0u2Wm7jfIZa7cK1+Dud9sXHkNwTZ/ZvlRF3Is6Ox1 8YDc6/i40/XwLBXWmKoiX8B8WUOqbxJbe566Rt+P8OdGzZ7ZtFXm3Hs64/OMeo9s2uVTciz4 /SA6XeXefSOrtMehtp0/R0c658eOHlU2z7HqmLxXp/efsI03g0Jt5puyRzad1VQ3eqeuFZA7 qhJf2PVF9F6/p3SfsAvA1OVF6qpkwxVVFymDIAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAANa3Ns9de9FXC2Wx3JVTsw xc4NlHkA80r1sPqdu5kul5uRa2VvbIvP5FUu7w56MvuiNGx2W8v5uyaiRpzZwaBqZVXiwj5V VPuJv0ljm+xT3gMgAAAAAAAAAAAAAAAAAAAAAAAAAAfhcJewt9RPnHZxOd8SKfua9uLWrQaM uc6LhUp3p/ooHmjxAXiXVG7FyqmvdI57uRid/cpcXg81dY/SN6Bdk2iuFPHl7HN5VkwnVfdK P2ed9ZubFL0XtK1U69fwi3+9OhK20aFte4WlKhtHcKSiSKVjUwj0cnVcAQnvRrCsZxCz6qtU bHpQua5evReVTaN2OIa46w29bbqyyup2Pex6yrGqIuF8ikGVV2zSU9yqpElqJahUqWeVUydl rbce96utNHpyKnhit1OiQxtbCiO7+mVAlK8cUN9doyn03p2jbHNyJH2jMo9OmOhH23Wh9Q7n bk0lu1FU1TX1aq50kueb/UsTwxcOFrgo6TVOqUZVTLh8EadML3pk7+SGCm4qbLBTRRxRsSRM MRETGAJQ2r2f0joagjjoqGKepYnWeRic2TSOM7UkNr0IlsfOxrKhUV7Ed1wi+Y7PfPf3T2go ZLfQvbX3Z/iMiidlWu86oV9tG2+5W+99ZfNT1D6G3c3NGyVqojmqBsk/FBYrToqOyWWlV6JR JF2isVMP5cKRfwyt9Mm9SanuGFihkWSZzu5PKhunFltzpLbnbegobNTI2uWVqSyZzzecivZ2 smpLTXWe2qqV10VrYlTv7+uALM2Whqd8t0J7hcEezS1pkWFkKewfIxenQsxbqKlt9FHR0cLI IIm8rGMTCIhqmzmlabSmiaSkhj5ZZmNln86vVOpuTnI1OvmA/GrmhgZ2s9SyBid6vciJ/qcB uobHI5qNu9Hlf75pSDi63svNz1RPpqzzyUdFTqrJEzhXOTKZyV8tF4vdXXx0aXipi7V2Od0q 4QCcN9KykfxG0E0VTG+NJ0y9rkVE8bzl7LZqCyJbabN2o/4lnfMnmPLjVuk9TWW4UTri2oe6 rVqwVLs4VFXouSXrFsDuhdrfFVRXyeOKRqK3LndwFquI692mfbCrbDcqWRVkb0bKir5T74dL 3aINraFktypWKj3dHSoilXqjhl3NmgWKa/SSRqvVrlcqGafhl3Np4kihv742J1RrVciAXk9M Vj/K1F88hh2o7GmP4Vo/nkKQJw17pI5XemOXP6TjDeGzdLkVPTFKifpOAvD6YbH+VqL55Auo bJj+dqNP/eaUedw2bpNbzJqKZVanROZx+EHDrurPA6R18qGK1ejVc7KgXobqGyImFu1Gq/DN Hphsf5WovnkKM0vDnurUZc++zxq3uy53U/b1te6WMemOXvz7JwEx8Ud4tc2rNKOhrqeRGOdl WyIuOpOVlv1mZZKJH3WjRVgZ/vm+YpFVcMG5FTI11Re3SqncruZcH7pw17pNaiJqKXCJhE5n dwFiOK282qfZu7QwXKmle6LojZUVVI/4Abnb6Pb+tjqq6CBy1Krh8iJ9JGVVwybmVVMsVRfX yxr3tcrlQ/Gl4YtyLbDihu7o0VfYx5QCwvF63TN52orZJaykqKunjVaZUeiuRV8xVCPaiwUd moKm76hdHLVwtlRkciLjJrO4+lNaaevzdN19ZVV1VK7lbEjlVVX3joNZ6eu2mVpoLrUzpPLG j0ic9csTzASKm2uiGscsupajkTvwqHHbt7t7hc6jqc56dEIgWeZy4bNLjzc6nPgtV6mhR8dL VvReqOTOAJRbt3t+9yNbqKo5l7s4P2dthodMf7RTe71QiWuornRxo+ogqYEXuVyqmThdvP5Z 5flqBtu5Ol7Xp6oZ6FV61UTu5yqmSyfCfuLtjoPScjrjWSMuMyo6RezzhfcKz23Rl5vFgfeK BJayKJFdKxuVViJ5VNg2x2e1NryjqKm0czWQO5XpheigXlTiS2u5Mei03X+7MpxJbXo1U9FZ un92VPThZ16qIvbY/wAqmF4Wteoqp23/AMVAti3iR2vblPRWZfL1j/7heJLa9yY9FZkz/dlT fWt699t/+KmW8LWvVXHbY/yqBbH1ye1/Lj0Vm838X/3MJxJ7XM8X0VmXH92VP9a1r3OO1/8A ip8v4XNetkRvaKufLyqBbROJLa9zV/hWX5v/ALnzHxJ7XJ4qXWZffjKmLwua9RyN7RceflU+ 14WteIv8b/8AFQLYLxJbXZ5/RWbzfxZlOJXa5Vx6Ky/N/wDcqevCxrxG57bP+VT59a1rz23/ AOKgWydxJbXNflbrN83/ANwvEnterceis3X+7/7lTm8LOvFX+O/+KhvC1r1Vx23/AMVAtgnE jtenX0Wm6dPYGXcSO16r/Os3Tr/F/wDcpZuBsNq/RunZb3cpF8GjcjVXCoadbtD3+r07NqF0 E8NujaqtldnD8eRAPQReJLa9yY9FZkz/AHY9crtcnT0Vl+b/AO55nrI9VVUe9E985FDS1tY5 zaaKaZyJ3N8gHpR65Xa78qy/N/8AcO4kdr1X+dZkx1/izzjfZLy2FXLb6pMd7sKdY9ZWOVrn PRU6KmQPS9vEptcq4S6y/N/9zDuJPa5f/wArMmF8kZ5y6VtFTf7tHbKWVyTy+w6ncQ6Ev/pp j05VwzUlbI5EYkiL4yKvRUA9A14ktr3Jj0VmTP8AdhvEntf3eisvT+7/AO5U2Phb165qqsit 6Z9iplOFnXmM9t/8VAtgnEltc3LvRWbr/dn03iU2vcuEusvzf/cqc/hZ14n++z/lUwvCzrxO 6b/4qBbD1ye1zXL/AArN82ZdxI7Xu6eisyeXpH/3Knpws68XH27v/NU+X8LevWsVySquPIjV Atl65Xa78qy/N/8AcO4kdr3dPRWZPL0jKl+tc172Pac65/F5VyfTOFvXqx83aqi+blUC2TeJ Ta9UX+FZen93/wBzCcSW1zevorN1/uyqCcLOvMJ9u7/zVDuFnXiLjts/5VAth65Pa5zVT0Vm +b/7mW8SW16Iieis3zf/AHKmrws68Rek3/xUz61jXnLnt/8A4qBa9eJLa5r1VbrN82fScSm1 6oq+isvT+7/7lSqjhd13CxXrLlETKryqRdBoa/VGr6nS9FDNVVsD1a/s0VcY7wPQN3Eptcv/ AOVm6eaM2nQ+7midYVPg9nubXS9yNkw3J5eamtU9juT7dUSq6Zns8L3L5jGmb3c7HdoLjbqy SGeJ6KmHL16gewKKiplOqA0XYzVEuq9vaC5T57VI2sevnVE7zegABH28GtrzpCnp32jTlbeH S55kp0zygSCYVyIqIuepXZ2+mtuRFTbW958viBm+etle5F21vePJ4gFijDlwiqvkK7errrV3 RNtb2i+6wyu+etVXCbbXvp3+IBYlq5TKArTduIjUtr5XV+gLvTteqI3nbjKr3HMZvrrXka71 Nb25HJlF5PIBYoEPbYbpam1NqNtuuei7na4HIv26ZuGoTCAAAAAAAAAAAAAAAAAAAAAAAAAC 9wC9wFb9TZ9ddGiJ/wAG3r+sse32Ke8Vw1MirxWR9URPA2fSWPYqYxnqiAZAAAAAAAAAAAAA AAAAAAAAAAAAAA0Hf6rSj2yuUqqqZYrf9FN+I04lnI3am4qrkTp5feUDzj0PY7ver9VVFmh7 WoopFmRvn6lhtW70ahv+2SaHgsT4q2GNI55XsVqJjv6r0NO4LFiTdKq7bkVnN15u72RYbjHr YrVt49LNTUUSTzMSaWOJEciKvXqgFKtJ6RqdS6lZZIJmo90n21znIiMyvXBYnW2hNvtBbQvp 4ayKrvzpolc/orm9euFNo2a2Y2wuGnKe6+jDZa2REdM6KfCp5z8eIfafQdk0HLdrXWzy1KTM TD6hXZRV6gSzt1uRpCg0Vboqu6I17I25z7xWbe3X89y3npqjQL31NblzEczvTPQkG/babfrs vJdKSrmS4spOdrUn/Cx5iDuFe92LT261LV32WONjHORz51yifGBYTZDh0e64Jq/cJ7q25Tr2 iQS+MjUXqhZyhpaahpWUtJEyGGNMNY1MIiGlJu5oDubqOhxjp9sQ4d13m0BR0skzr9RucjF5 USROoFZOP29RVesaPTsb8v5WOVEU1bhF04657r0yTQI+K2SJle/vOlu1ZFutu/dblLL9opIn Pjcq9MIvQm/gPtbW6g1ZWO5XtR7OzcBbVjUY1GtTCJ0QxIicjlx1RFPo+ZFw1Ux3ooHl1vnb pq/eG50lOje0kqXo1FXGVypnRmzOtbzquntzbesSc6K+RPYonvn3vfFW1O9VbHbWuWq8Ld2a J+NzdCwGmNztfWzScei36Sqk1FIxGRV6U/itVe5V/UB2O9r6GbT9i20tFDFctRxRxos+MrEj ei9ULB7QWO6af0Db7Xd6l89XEmXvcuV6+Q1bYvbBumaN17vqpV32sXtZZH9eRV70TPcSwBhy KqYRcGQAMNRUVcrnIRF5lXm6eYyAMKi8yLn9QaiomFXJkAYVF5kXPRPIHIq4wuDIAGGIqIuV yZAGERUcq5znyGFauVVHKnTB9ACqOtqObQe/kmq9X29K+x3CVOwqHt5lp8eVPMR/xWbW3q+X qm1lpdvonZ6mJFa5q5VnN3JhC62r9N2vVFjqLTdqds0EzeVenVPeXyFbFq9X7FXmps8luqNR 6brEc+ljjZzrE9fYoqr5gKb3/SN5002nnvFO2FJXYY1V6/rQs1oPefbq26SoKGt01QSVMELW SPVnVyp5SE995NX3XUCXfVFBLRNq34gjczlRv6jftG8KWs9R6cpLzS3uhiiqY0e1jmrlEUD8 +IjcvReq9N09HYLLSUk8blVzo2YUiK3bd6nrrSy6UNElTTvwici5VFXu6Ib5vLsDqXbSyw3S 7XSlqoZnK3liTqh3fDXqfWGg45Ly+wVN30272cTYuZedfY4UCT9gdPN2i27uF+1xCxy1sCsi oneNz+5g3LhO0zqCG73nVUtOtus91n7alpW9G8i+4cXb/T2oN3dVt1bqullobHA5H0dBI3lV rk86eVCytHTQUdMympo2xxMTDWtTCIgH3yux7Ne8yqLzIvN08xkAYwvNnm6eYORVRURcGQBh UVUTDlQyABhqKiKiuVQ1FRMKuTIAxhebPN08wRFRyrnKL5DIAw5FVMIuDD2q5MI5W+8fQAhL iz0nqLUuimpZnvljp5WSzU+fFe1q5XJody9Cd1Nknae0nTxWy6W+JUkoWpyI5yJj/VS1EjGy MVj2o5rkwqL5SvW8+2Vx0/e/VB0HmGrhXtKumYnSVqeRGp5QKS3Pa7WVubUeGWzsUplVJFcu E+M2nhp1jp7RmorhNqS2wV0T4uRrZW5Rq58hJm924OvNwNKtZbdMVFqoqdnLcXyQYV7/ADop D2yu1l63QvlXa7RWw0ktM3nkWVO8Cw913y2zktdTHFpi39o5io37X7hVSkslbrDUVclkgYr1 e6RI84w1V8hPV04P9bUNvmq33+gc2JiuciNXrghnby16npNdPp9NxvnuVDL4yMblHYXzeYCQ +HrZzV1Vr+muFdSrQ0FC5VnncvLj4yYtzFp9x9zLRZtCULX1NqljdVXFrcOVrV6pnyn6VGtd f7h0NJoC3WGeyVyojLnWuh5WOVPNjuJ/2o0BaNB2KO30UPNUOTnnnd1c569/XzAbTa4JoLZD BNM6SVjERz171OWnd5wAMIioqrzZRfJ5g1FTOVyZAGFRVVFRcYGF5s83TzGQBhUVUVEXHumU RcYVcr5wAPlGryY5lz5z6RFRMZyvnAAwxFRMKuQqLzZ5unmMgDrdQUVRW2Guo6ed0c08Ssje ne1V8pV7Z6ah283Nu9j1lb42XG5SO8EuD25VyYxlV8hbM0PeDbe1a9sUlPPGkVaxMwTs6Oaq de8CjO++zerbfrmpq6SldW0lbIr4pUXPslz5CI7/AGGv0/XtorjG1k/MmWoucdS4bNf6/wBF W6o0JdNN1N3uK5joqxsHM1qdzc5Km7jR39msap2po3MuL5UV6KmERc+YD0P4TUVu0dJyJ+En 0EvERcJn3pKT3/2EugDDmtd7JEX3zIA+ezZ+I34h2bPxG/EfQA+Fij7+zbn3j5SNvKruyZze 8fqFVERVVcIgFTONrWb7RqCx2umc1OaSN78eTDiyeg7tT3rSVvuDGtVHwsb069UQ88eLrVHo 9uvUtjervAHujTr5lLbcFOp23raWko5XK6op1XmyvkAndGMRco1EX3jIAAAAAAAAAAAAAAAA AAAAAAAAAAL3AeQCt+pkzxWxoi/8G3p+ssexERM46qhXDU/TiujVv9Sb9JY9vsU94DIAAAAA AYa5ru5UUDICKi9y5wYVzUXGUyBkBVREyq4MKqJ3qBkBVREyq4GUxnyAAYa5HdyopnKZxnqA ARUVcIvcEVF7lyAAVURcZCqid6gAFVETKr0MNVHJlFyBkiXizVybO3DlcrV5k6/GS0ioq4z1 QiPi0VV2cuHKqezT9oFANmqO53LXsFstt5ltUlTNyLOx2FTqTbp7Rd21Xf71pfVGta2e2UT3 80rly1eVCsEFTLS1r54JpIpGvVWuY7Cp1LdbG1emtabS3LTNinkptRypzyvnky+VyJ1x5QII guUNh1ZNZrHqytp7YkixrKxPdwpK+5W1mp6fa6HVKa0rbnbZnMVrHu6dV6ELVO3+tItQTWRb BW+EPmVqPWJfP3ltdeafr9K8KlNbrrM/t0WFz2uX2OFToBrGlOHjV160xTT+nGvZBPGirEi9 ERUIJ3l2w9IGo0oa64SSdple0XvUstZOKLSWnLRaLJBSzzPYjGzyIuWomOpH+51Lb99Ny6Om 09VNzK1zk5nZx7gFbLXT1FTdaakWokZFNKkaPz3JnvJw3F4fKjT22aa0ZdaisiRjXKxe5MnH 0jw+a8qtaQWyppnQUlNUI50zmKiK1F8ilytwY9K6S2aktGqpEkoIqfkWPm8Z6p5gKKXnQs+j 9vqfVdpvknb12IpIWKmUaqdclkPsflM+Oz3qV87nq/lyi++VOZqm20mprjJStq5rVIjmQQyv 5kb5lwW74CXpNZr1M1MNcrVRPN1AtAYf7B3vGT4k5sLjuwuQPPGupmT8UL2KidK1Xf8AyPQG K3UbpIKtaSN06Mb9sx1ToUEXxuKWXvTFWv1j0Hpf5NF+gn0AfoAAAAAAAAAAAAAAAAAABxa+ ipaxrUqaZkyNciojk7jlACmX2QqJkc1gc3Cfb+iIhZLYVyu2ssiqufuVn0Fcvsh6qj9P9Onb rksZsGqLtZZMd3grPoAibj7djb2iRU6do7qd/wAIdFTVO0EMFRAyaN6NVWuToqnQcfqJ6ndF lF/jXG0cHKI7aenRfxW/QBNFJTw0sCQ08bY407mtTofqAAAAAAAAAAAAAAAAAAMSMa9iseiO aqYVFMgCPd5LbR0+2d3jp6eOBsjVc7lTvXClXfsfmU3L1E1vkY7r+stbvbzepvdOb8RcfEpV P7H5n1TdR+bkd9YC52rumm674F30KUe4Q0V3EHfFVEyjnfWLw6u/o3XfAu+hSj/CFn1wd95u vV3d+kBeqmt9HDVy1MdLGyaRcueidXHLMNaiKq+cyAAAAAAAAAAAAAAAAAAAHDmt1HPWtqZq SN8rMK16p1Q87eNCJrN3al6ImXTdT0ePOTjSVPVan+GAt9wmfekpPf8A2EukQ8J2fUjpOXv5 k+gl4AAAAAAHEvEEtTbKiCCRY5HsVGuTvRTlgDz6372KqrLq9a19ylmkuc/MvMndzKWW4Yto 6zbWCZ81wlqYamFqtY7uaq9ToeLDHpisa8y57RnTP5xYS0/zXSfAM+qByQAAAAAAAAAAAAAA AAAAAAAAAAAAHkAXuArdqfpxXRqi9fA2/SWQZ7FPeK4amynFZGqIip4G36Sx0fN5cYwmAPoA ADpNbX30u6eqbr2Kzdgzm5E8p3Z+c8ENREsU8TJWL3tcmUUCvnrkkVVRLC/p07nH5TcS9JSI 1Z7IsSyLhuUVMqTz6XrF+R6D5hv7itPGRqC06auGnIKK3ULHsqvtqJE1OnugbE3iQbyo5tgd h3Xojupj1xzM5XT7s+flcSvt3R2K8aKtdw9CqBzpqdrnYgb3/Ed6un7JlMWeg937Q39wEGLx IIqYWwPX/K4LxINXvsD1x+a4nT0v2P8AJFD8w39xh2n7J05bPQe79ob+4CDF4kEVMLYHr/lc YdxJNRMLYX4X81xOvpfsf5IofmG/uHpesX5HoPmG/uAgpvEe1vsbA9P8rjPrkGpl3oA/Pn5X E6el+x/kih+Yb+4el+xfkih+Yb+4CCm8SLVTKWB/X81xlOJBrUXFgen+VxOnpesX5HoPmG/u HpfsX5IofmG/uAgpOJFrkR3oA/3PFcZXiQRe+wPX/K4nT0vWL8j0HzDf3D0v2P8AJFD8w39w EFrxIIqYWwPVP0XBvEe1qYbYHp/lcTmun7JlMWegx5ftDf3GfS/Y/wAkUPzDf3AQX65BEXKW B+f0XGib7b4t1Ht5V2tLK6HtHIvMqKWv9L9j/JFD8w39xFPFZabVSbP18tNa6OORHJhzYURU 7/MB5ro5HTrlne9VN1sS6p0rXUeprFBU0vZoirJG1eqGo0rmrcWNVvdL1+M9P9rdPWS77PWe nrLVSPbLRNa5eyTPVO8CD9EcTdkrqSnmuFkgkvbURj3KnjLjymrcT29tTqvSC2OO0upopXNV 8mF6dTot/NpbvtNq9mrNMUfhNuWXna1zOdGL3rze4SJpO6WLiC2uqbC6loaDUcHLhWsRnMqe YCvdnqrDBJZofS7FUvdO3tlVF+2p5lN82urmac4kbfU2m1NpaeocqpSMXow6i76e3O0hfKO1 +l9lWtLOi08sdNzJlO7K+Yl/bjStToyprN3Nzlp2VjPHpqaNOXGU/FUCzGttY2jSWmH3u7zM gakfM1ir1cuM4KI671XrLiB3ASz2Rky21JeVjGr4vLk4ur9Waz4gNw0tVvWRKFZeVrI8o1rM 96lzNg9oLPtnYWxRxskuMjUWeXGevuKBRviM26h23uVFaYlRZXQMfIv5yp1Qsj9j9/o1df8A IRn9kHT/AMQaZV7vB2Em/Y/8elu68vd4gFozD/YO94yfEjUVqr5URQPPd6qnFLJhM/da/WPQ el/k0X6CfQeez2udxSS9f+LX6x6E0v8AJov0E+gD9AAAAAAAAAAAAAAAAAAAMOVUTomTIApv 9kPdh1gb551LF7DZbtXZORM/crPoK6/ZDsc1gTHfOvUsZsJ02ssif8qz6AIk4/VVNu6H4Vxt HB0qptPTqiZXlb9BrHH5n1O6Lu/jXGz8HmPUmp859i3uAm5O4BO4AAAAAAAAAAAAAAAAAAAB o+9n3t7r42fEX6FKp/Y/srubqJE7kY76xa7e/wC9vc/g1+hSqX2P1P8AxM1Ev5jvrAXM1a5F 03Xonkhd9ClIeEFF9cFfvG8r/rF39XIiabrvgXfQpR7hDVfXB33r+E76wF9muRVVE70MhEQA AAAAAAAAAAAAAAAAAAAPOTjSRE3bnVPLMejZ5x8aS53bnTHdMBb/AITPvSUnv/sJdIi4TPvS Unv/ALCXQAAAAAAAYcuGquM4ArlxYMzqOxPz3SM+sWFtP810nwDPqle+K93+0NiTC9ZI/rFh LT/NdJ8Az6oHJAAAAAAAAAAAAAAAAAAAAAAAAAAAeQDyAVu1Qrm8V8aeTwNv0lkGexT3iuGp lzxXRoqZTwNvX9ZY9vsU94DIAAAADD3I1iucuERMqecXGtqhbvu5WUML+aClVqsVF8p6LXKK Sa3VEMS4kfE5rV91UXB55b9bI6ytmr4rldammkS71CxwK12VRc+UC0/BrqVNQbWxR8/MtFyw r19wm4rxwh7X6t26tcrLvU08lJWr2rWxuzjp0LDgAAAAAAAAAAAAAAAACJOLVFXZy4YXHjJ+ 0lsiXiz+87cP0k/aB5oUafwnH4v++7/1nqpsa5F2tsWPJSt+g8q6PHoozvz237T1U2Pwm1li Xon3Kz6ANj1LZKC/2eotlxhbLBOxWuRyZ7zz7Yx21nEdM21zrHSRTOwxvcjS8u7WvLXoPSlT da+drJEYvZMVernFDNDzw613XuGtdRSpBZ3Okc7nXCrlOmMgWBvHELdK+8Nk09pSO52uiYkl TWcyJy49l0ID3+3buu7GoaO1W5XQUiuRiwNXovU6Cs3NTTtzulo0oxq2Wq5opO1TxlRV64NP uEtuoauju1ie/tGOR8qOXy5z0A9DOGjaO1aA0zT1vYsfcqmJHPlx1wqZwTEQjwz71WnXun6e 21MrILnTxoxWuXHMiJgm7KdwFD/sgyqu4NM1V6dgwkz7H+iJpu6oi5TxCM/sg+PT/Td/N2DC TPsfyY01dc/mAWkPmRyI1Uz1VFPo+JGoqK7yoigee0vN66STl/ra/WPQil/k0X6CfQefL+b1 0svL/W1+seg1L/Jov0E+gD9AAAAAAAAAAAAAAAAAAAMORVTouDIApv8AZD/ZWBM9e3Xp5yxe wzV9SqyIi4XwVn0Fc/shrG9pYXKq/wAepY3YPHqWWTH9VZ9AES8fqKu3dD7krjaeDpVTaemV EyvK36DVuP7PqeUOPbXG08HHTaimz+K36AJtTuAAAAAAAAAAAAAAAAAAAAAaPvaiptvdMrnx F+hSqv2P375eosd/I7Pyi1e9reXbe6dV6sVf9FKp/Y/V/wDEzUSL+I76wFzNWuRdN16IvdC7 PxKUg4QceuCvvKmUy76xeDV2PS3X4x/Euz8SlH+EJUXiCvvRU8Z31gL7J3AJ3AAAAAAAAAAA AAAAAAAAAB5ycaf32p/hT0bPOPjSz6rc+e7tugFveExrvUjpE5vwv2EvkQ8J2fUjpOXv5k+g l4AAAAAAAACunFh/SCx/CR/WLBWn+a6T4Bn1SvfFg1V1HY3cyYSRnT/MWEtP810nwDPqgckA AAAAAAAAAAAAAAAAAAAAAAAAAAvcB5AK36lcvrrY2p/U2/SWPb7FPeK36maq8V0aov8Awbfp LIM9iiZ8gGQAAAAAgHi2ciV+kEV2Pu1ehPxAHFuqeH6QRERVStVV94CatJqnpbt6ZyqwNO1O r0nhdN29cf7hp2gAAAAAAAAAAAAAAAAAiTiz+87cP0k/aS2RJxaJnZy4Jn8JP2geaNI/+E2N XyTd/wCs9PtvL9bNObH2m73WdkNNDRtXLl71x0Q8wKaSJlwa6TPK2VVd8ZKe5W7941TpS2aX oXPgttHAkcnLlObAHK4gdz6/c/WsiNldHZKd/iRZ6Jjymq2W26h1ncYNL6Yp5ZolcjXNjToq Z7zpdL2a6anu0FksVPJJLM9Gq5G9Ez5VPRPhv2ht+3emIXzwRvuszUdNIqZVrvcUDSdquFjS dr0/yangjuFdNF1VyYViqQLxGcPl10LVzXmxxPqrO5Vc5Gp0iTzHodhM5x1OLdrfR3Sgloa6 Bk8ErVRzHplFA8mtLX256WvEF6s1Q+KWF6K9jVxnB6GcOW8to3DsEMM1QyO7saiSxqvVVK1c UGwtbo24S6k05C+e0zOVXxomVYvevRO5CB9J6ju+lr8y82Sd8EsTsujR2EX30Anv7INL/wCJ NNHj/hmLklH7H8qrpu6qv5hVHefcav3Nv1NdKyJEqIoGxORid+PKWv4AGq3Tl2avenIBaM+J EXCrnpheh9nxJzYXHdhcgefD0VeKWTC4+61+segtKi9hGuenI3p+o8+Xrjilk/xa/WPQel/k 0X6CfQB+gAAAAAAAAAAAAAAAAAAGHKqJ0TJkAU3+yId9g6Z+3r+osZsFj1K7Jj+qs+grp9kO ROawLnunUsXsJhNq7IvdmlZ9AES8fqqm3dDjyyuNo4PE/wDCan6Z8VvQ1fj9XG3dD7srjaOD pEXaenRVx4rfoAm5O4BO4AAAAAAAAAAAAAAAAAAABpG9njbcXTm8XxF+hSqf2P1V9U3USYyn I76xa3e/rtvc/g1+hSqf2P7ruVqJE7+R31gLmataiacr8J3wu+hSkHCE5E4g77jrlzvrF39X L/s3XYX/AHLvoUo/whtX1wV97k8Z31gL6tRUVVVcovcZCKgAAAAAAAAAAAAAAAAAAAAecnGn 99qb4Y9Gzzk40/vtTfDAW+4TPvSUnv8A7CXSIuEz70lJ7/7CXQAAAAAAAAK58WCM9MNjVV8b tGYT/MWDtP8ANdJ8Az6pXviwYi6isb89UkZ0/wAxYS0/zXSfAM+qByQAAAAAAAAAAAAAAAAA AAAAAAAAAC9wHkArfqZG+usjyuF8Db9JY5jURMp3qhXDVKJ666NUXp4Gz6SyDPYp7wGQAAAA AgHi1X+ENIoieN4YvUn4gHi3w2u0g5c5WtVOgE06TV3pct6Kn+4blTtTq9Jf0at/wDTtAAAA AAAAAAAAAAAAABEnFoqJs5cFX8ZP2ktkScWaIuztwz+Mn7QPNChpW1t08HdJ2TXyKivxnHU2 K+U1Kk9JZLMqTSSq1j3t8rlXB3eyd/sVhvVylvluSsjkbyx5j5uVcr1OBqJKjT+uYdRMhhWk qJ0qIWN7msz3KnkAvLwq7NUWhtLwXK407JLvUNRznub1Rq9UJ3I72N3Hs2v9K01VQTt7eOJr JIs9UwmO4kQAAAOFeLbTXWgnoK2NstPOxWOa5M9FPPXii2lft1rBt0oY+e1VknMjETpGmT0R qqiGnhklnekcbG8znL0REKHcZ+7dBqq7x6as6pLFROVk0nkXr5FA3DafZvRV023uOs2QxyOb RPxH+K9G5ybVwJoiUV/RqYaj0RE/WQft1xBppbQNTo6OkjfTTwOZ2it8ZHKmCbuA16S2u+TN 9i9zVT4wLPmH+wd7xkw/2DveA89FfnillwmfutfrHoRS/wAmi/QT6Dz2e7HFJKrU/wCLX6x6 E0v8mi/QT6AP0AAAAAAAAAAAAAAAAAAAw5FVOi4MgCm/2Q5EVbAi9/brgsXsI3O1dkRyf8Kz 6Cun2Q5uZNP9cYqFLG7CqnqW2Xr/AMKz6AIk4/cJt3Q5T/euNp4OUR21FMi93K36DV+P1cbd 0PTP21xs/B1lNp6flxnlb3+8BNwCdwAAAAAAAAAAAAAAAAAAADSN7mo3be6Y8sa/QpVP7H8i ruZqLK4Tkd9YtZvYnJtxdF78sXv95Sqf2P5P/EzUSqvTkd9YC5urGomnK/HTMLvoUpBwhIqc Qd9z18Z31i72reb0uV/NjHYux8SlIeEFv/mCvyZ8rvrAX0a1EVVTvXvMmGuRVVOvQyAAAAAA AAAAAAAAAAAAAA85ONJUXdudEXumPRs85ONJE9Vqf4YC3vCcirtHSYXHjJ9BLxEXCZ96Sk9/ 9hLoAAAAAAAAFcuLDl9Mdjz7LtGfWLCWn+a6T4Bn1SvfFgxF1HY3eVJGfWLCWn+a6T4Bn1QO SAAAAAAAAAAAAAAAAAAAAAAAAAAA8gC9wFb9Sonrro17/uNvT9ZY9vsU94rhqTrxXMTu+429 f1ljo+byp0wmAPoAAAAAIA4tnKlw0knkSsVSfyAOLZ2K/SKY/wCMUCa9IrnTNvX+4adodXpL rpq3/ANO0AAAAAAAAAAAAAAAAAEScWqqmzlwVEz4yftJbIl4svvO3D9JP2geaVFc6q3TVKUz 0akqq1+UzlMnb3ej1M2yR1tyoZ0oHoixyub0x5Do4Y2S3BGOz40qovxnpXt/oHT+p9j7Ta7l QQPSSjaiPVqKqLjvAoLsxuXedudTRXK3zP8AB3ORJ4s+zb5j0k2j3Fs24WnYLnbKmPteRO2h Rcqx3mUoBxC7K3jba9STxQvntMj17KREzj3/AHDWtpNy75t5qCG4WqdywK5O2gV2GOA9Wz4n ljghfNK9GMYmXKvkQjLbXejSOrtMx3H0RiglbH9ta9yNVF8uCu/FPxEyVjpNLaOqnJEmWVFQ 1cKi+4oHN4s+IZHJNpPSNWmFyyoqGLlFTuVpUa0W65368soKCKSrq6h+ERvVV6mbZb7jqC8x 0NFFJVVdTJjOMqrlXvUv3wubB0GirXDe73A2a7ytRyo9M9mvuAUr3W0BXbfXKloK9+aieBsq tVMK3PkLcfY/f6NXX/IRH9kEVPVdp8Y6UjOhLn2P9c6buq4x7AC0hh/sHe8ZPiRuWquV6IoH nwv/AKpZf8Wv1j0FpVXsI0x05G9f1HnwqK7illz0+61+sehFL/Jov0E+gD9AAAAAAAAAAAAA AAAAAAMOVUTomTIApt9kPRFfp/Lsfb1LG7DNRdq7Ii9U8FZ9BXL7IcirJYVdjCTrj3Sxuwa5 2ssi/wDKs+gCJuPzpt3RdcfbXGz8HnXaan6Z8VvQ1fj9RV27ofclcbTwdZ9Sen5e/lb9AE2p 3AJ3AAAAAAAAAAAAAAAAAAAANI3tRU23umVz4i4+JSqf2Pxcbm6j6Z8R31i1e9qqu290zj2C 4+JSqf2P5V9UzUKIn4DvrAXN1YjvS5X5XP2l2PiUo/wh/wDqCvvXPjO+sXh1cv8As3XYX/cu +hSkHCDheIK+qieV31gL6oAncAAAAAAAAAAAAAAAAAAAAHnJxpKi7tzoi90x6NnnJxpInqtT /DAW+4TPvSUnv/sJdIh4Ts+pHScvfzJ9BLwAAAAAAMOXDVVEyZAFcuK9y+mGxJj/AHkf1iwl p/muk+AZ9Ur7xYf0gsfwkf1iwVp/muk+AZ9UDkgAAAAAAAAAAAAAAAAAAAAAAAAAAF7gF7gK 3amyvFbGmcJ4G36SyDfYp7xXDUyJ66yNVX/g29P1ljmORfFTvREA+gAAAAAgDi4VFrtIpjql aqk/kA8WqJ6IaRXy+GKBNWkVzpm3r/cNO0Or0l/Rqg+AadoAAAAAAAAAAAAAAAAAIk4tcrs5 cMLjxk/aS2RJxaKjdnLgq/jJ+0DzRo1xco8uTHbftPVPY97fUssS5THgrPoPKqnjR1wb42Oa XHvdT1R2IgSPaqxNVyvzSt7/AHgO811pW16u09U2i5wMkjmYrUVU6pk83uIbaWr2z1X2Cosl vqFV0LkTo1uT07qJI4YHySvSNjUyrlXCIhRDjh3ItWpL5TWC0rHUJTIrJpfxVz5AIBt9lvMr l9CXVMlLy5lmicqManlycKotkkt1jt1FKtVNK5GqqLlVXJu+hdy5NH2Cs09FaqSrgrolifPJ 7JnN3qhqlnuMNg1bS3SDEzGSo5Ud5sgXl4VdiKDR1siv15jjqLpOxHJlPYovVOhYp68jVRG9 Eavd5DTdntbWbWmjaO4WyoY9zImskZnxkVE69Db6mVraOWVVw1GKv+igecXGPcp71vFKj0X7 VHy/qRSwPAG3l09dm+blIFv0MWrt6NQLJiRKeKRU8vcqlgeBZnZUl/h/Ec1P9QLNnzIqI1Uz 1wp9HzIicqrjrhQPPZ+fXSyYXH3Wv1j0GpWp2EbvKrG/QefOMcUsuV/4tfrHoPS/yaL9BPoA /QAAAAAAAAAAAAAAAAAADDmo5MKZAFOPsh3LzWDm9vXBYvYNUXayyY7vBWfQVz+yH55rB0Rf t6ljNgsepXZP8Kz6AIl4/UVdvKHHtrjaeDlUTaimVVx4rfoNW4/lX1PKHHtrjaODv709PhEX xW94E3AJ3AAAAAAAAAAAAAAAAAAAANI3uajdt7pjysVf9FKp/Y/M+qbqJe5OR31i1m9vN6m9 05kx4i4+JSqn2P7puVqJe/LXfWAuZqxqJpyvx5YXfQpSDhC68Qd96fhO+sXf1f8A0brvgXfQ pSDhCf8A+YO+qnlc76wF9U7gfLW4VVyq5PoAAAAAAAAAAAAAAAAAAAB5ycaf32pvhj0bPOPj STG7c65z9uAt/wAJn3pKT3/2EukQ8JSou0lJj8b9hLwAAAAAAAAFceLBqLqOxu5k6SM6f5iw tp/muk+AZ9Ur5xYKz0w2NF9n2jMfKLB2n+a6T4Bn1QOSAAAAAAAAAAAAAAAAAAAAAAAAAAA8 gAFcNTRSrxWRuSJ6t8Db43k7yxsaL3qqYwmDr5LFaZLv6LPoonVvLy9qqeNg7IAAAAAAEOcS GlrvqOq02+2QulbS1Svl5UzhCYwB1+moX09hooJUVHsiRHIvnOwAAAAAAAAAAAAADR91NwqP Q0dG6qYjlqVw34zbbPWNuFqpq5qYbPE2RE99AOWAABEnFn9524fpJ+0lsiTi1ymzlwwmfGT9 oHmhSNzdGde+Xu/WeqWyj2x7TWR6vRrWUjVcq+REQ8rqLHopGrkRE7Xqv6yz243EG227U2vS GlZVbU+CtZPO1cOavlQDb+LPiEipYajSGlKlHSPRWVFQxcoqL5E8xUHTNhver7+ygt8U1ZVT O6qmXL75+umrDetZajjt9HDJU1dTJ4z8KvVV8qnobw37J2vbuxxVdXAya8StRz3ub1jXyoig Q5oXg/SWwsmv9axaqRuURMpy++QpvrsbqDbmtfVKx1Za1XLZY2rhie6p6aNbhqoq5Or1Tp61 6kss1qutLHUU8rcK16ZQDzF2O3UvW3GpGVlHNI+jcqJNCq5RW+XCHoBat0tPaq2sqNQ0VXGx UgVZYld40aqncpSTif2cqttr++tpUc+0VL/tb/Mq+Q0Khk1pZbBigfWstlemVbEiq16e6BKG wFE+7bg6zrmtc9qUs70d+tSfuBlean1Avf47fpNQ4TtB3C07Yak1VcYnwyVFFMxrXphVRU7z bOBP+Rag+ET6QLOnxIuEVMd6L1Ps+ZHIjVTyqigee0rVdxSSIi/8Wv1j0Hpf5NF+gn0Hny9y JxSy5/ra/WPQWlT7RGueisb0/UB+oAAAAAAAAAAAAAAAAAAAGHORqZUCnH2Q9FV1gci906lj Ng/vWWRf+VZ9BXP7Ifzc2n1TuSdcljNg1ztZZFx/wrPoAiXj8VU29os9yyONo4O0Rdp6dHd3 K01jj9XG3dD0z9tcbRwcoi7UUyL18Vv0ATancAAAAAAAAAAAAAAAAAAAAA0je3m9Te6cy58R cfEpVL7H47G5uok87HfWLXb2K123F0690ap/opVH7H8ieqdqLP4jvrAXN1Y1G6cr188LvoUp Bwhovrg77lfwnfWLv6tVy6cr8pj7S7HxKUh4QkxxB33y9XfWAvoiovRF7jJhqInVE7zIAAAA AAAAAAAAAAAAAAADzk40/vtTfDHo2ecfGiq+q3PlOnbdALf8Jf3pKT3/ANhLpEXCZ96Sk9/9 hLoAAAAAAAAFdeKyCWTUdjeyB8iJIzKond4xYG1fzXSfAs+qh+N0s1rub2Pr6KKocxctV6Zw c5jUa1GtTCImEQDIAAAAAAAAAAAAAAAAAAAAAAAAB12o7tT2S0TXKqVUihTLsJnoB2INN0Lu ZpHWLX+g9zje+Nytc168qoqe+bLeK1aO1zVkLEmWNqqjUXvA5p10V9s8tzfbY7jTurI1w+FH +Mi+8VuuXEvqykudRSt0MkjIpVYjuZ3jIikJ2DeDUVLvfc9UR2RZp6mVHOo1VcR+4B6HA0LZ DXFy15peS73K0+hkjZljSLK9U8/U30AAFVETKrhEAGEVeZUwvTylbd299b0/Vb9IbfW30SrW KrZXouOVyd6ZNYbe+JR3dp13Xqn24C3OV5sYX3w5cY6KuSoy3riURcel12fhj85tx99dHO9F dSaZV9DF40uZM4QC3wNN2i3Ate4Ol4rvb3I2TlTt4va3eY3IAAAAAABeiKoPwuLpGUE7oUzI jFVqe6BAvF8iuprG5GZ8de9PdJn0Sn+ylpyi58EZ73cUN4jt4tRVWsJbBXUvJ6GyYaqu6qT1 wjbqag15y0tbRJFRUkPZI9HZRVRALJAAARLxZfeduH6SftJaIk4tVVNnLhhM+Mn7QPMp0cr5 plja53K5VXHk6nY6WsNy1JeIbZbqeWoqJXo1OVM4TPedroy4Wijp73Hc8dpNErYFVO52VNt4 adf2zQe4UFdcqSOaB7uXtXfg5Autw37J2rbuxRVdXDHPd5mIskiplGovXCe6TOdbpq+W6/2i G5WyoZNBK1FRWr3HZAAABWf7II1q7Y0qq1FXt+/HuGwcN8en4uH211t9paLwaKny+WaNOn61 Ne+yCPam2VK1V6+EfsODpewXXUnBzBbbKrlq3U7VbG1fZ4XqBukm9Gg77p6/2C2zQ0axUcrW LlEa9cKnTBq3AphKPUGFynaJ1/WQjcLFc9R6Ndp+1aIis9ytqdpVV0aqjpGtTrkmvgNY6O1X uJ/VzVair+sCz5h/sHe8ZPmRV5VwnTC5UDz1fhnFJL5c1a/WPQil/k0X6CfQees0sTOKORZF wnhip+vmPQql/k0X6CfQB+gAAAAAAAAAAAAAAAAAAAACm/2Q9VR9g83brksXsNn1KrJydPuV n0FdPsh7+V9gTGczqWN2DVF2ssmP6qz6AIl4+8+p3RdU/jXGzcHiuTaanVvfytNY4/UVdvKH HtrjaeDZyLtTT4Xua36AJtTuAAAAAAAAAAAAAAAAAAAAAaTvf97e5/Br9ClUvsfvXcvUSL3c jsfKLWb2eLtxdM+N4i/QpVP7H8q+qZqLKdOR31gLnau6abrvgXfQpR7hCRPXBX3GV8Z31i7+ rOZdOV6KmPtLsfEpSDhE8XiDvqJ08Z31gL7J3Aw1yKqonehkAAAAAAAAAAAAAAAAAAAB5yca f32pvhj0bPOPjSVF3bnRPJMBb7hOajto6NF/GT6CXiIuEz70lJ7/AOwl0AAAAAAGEVVcqYXp 5SI+IHeGDb2nit1BAlbeqlE7Gn86L5SIIdUcRlzalZSabc2GXqxO2x0At2qrzY5V98wjlwni L1KkJeeJVXK30uuyn98fD9T8RtC1amo0250bOrk7YC3gIX2B3pZreeaw3qlS33umXkdD+Mqd 6k0AAAAAAAAAAAAAAAAAAAAAAA49yoqe4UUlJVMR8UiYcinIAFa9xeGiJap930Hcqi213Msi sWZUYq+8hq1l3X3O2xqktWvLPPdLZEvL21PCqpj3VLeqqIiqp116tNuvVG6juNHHU08iYcjk A0DbncbbfW8LJKJLbDVPX+Imaznz7xB+haSik4wNRwrR07qdKlOVnInLjHmN13B4Z7bNWvvO h699grmeO1IU9kprfD7tVuBp3dapvuq2SzpJIi+FPXrJ7oFqqWmp6Vix00EcLFXPKxqNT/Q/ UAAdPrR1S3S9etJzdskS8mO/J3Bh7WvYrXJlFTCoBV7g1htU181PJWpFJd0uD+kmFeieUtDy onkQrFunsnq2zasl1ftjcpqSsmcr5YIunOqr1OlbVcSTI0RbdUucnRV7ROoFt+VPMdTquC3S 2GuS7MhWj7Je0V6dEQrEkvEmrf5vqcr1T7Yhw6/S/ELrOH0Iu1RV2y3z+JO5HZy3ygd/wcu5 dYazitjua1JcVSPC+LjyYLQmg7I7b2/bnS7bbSqklRKiOqJcdXu86m/AAAAAAAw5cY6ZyuDJ 8Pljb0dIxF8yuwB56ccumvQzct91ZGjW18meiFjOBrTPoLtc6omh5ZqibnRyp+CqHT8bejna lt1oqaGOJ8sT8yKjk85Nu1dDBZtBWeja+JFSkjV3jJ34A20H5Nnix40saL+mg7eLm/jYsefn QD9SJeLP7ztw/ST9pKj6iNE8WSJf86ET8WEjX7OV/I+NzuZOiOT3QPNi1UTq68x0aKieESqz K+TqbhuhtVqHQ9LQ19VC6aiq4klbPG1eVnuKvnNd0j11bb0/5n9p6Zelazaw2ot9ku8VPLDJ SJhXKniux0UCkHDhvldNuruykuU0tTaZVRrmqvNyp7hfbSW4mltS2Nl0oLrTMjc1HK18iZZ7 innTvZtPctv9Yut0qpLbqiXEE6OTyr3G/wChdiNypLXTyWm5yU1trWo9XNlTuAutV7maHpZu xl1Hb0enRU7ZDn0Ws9L10CyUl9oZERM9JUUqvTcJlI+jSW86zVldJ3Iruqr8Zq+rOHTczTKK mkLnUXGF3R3K/oiAdpxt7i2/VdXR6KsUrKuVJkXnjXKKq+Qsjw22CtsOz9moK5qNnSBOZqp3 EL8P3DLNbLxFqbWj3TVbVR7YJEzyu785LYxRsijbGxqNa1MIiAa1ryho6fRF8lgpIIpHUUnM 5jERV8VfKQTwJ/yLUHwifST/ALif0Evf+Ck+qpAHAn/ItQfCJ9IFnV6Jk1XcbXdh0PY33K91 DY28qqyNXYc/3jma61HT6Z0vW3mbCpBG5zUXyqidx5o717q3vcnUS1NylfFQxyL2MHNlGJkD so9UWq+77svrZfB6N9YkiOeuMJzZPSbTV5tV4tsM1rr4KuPs2+NE/m8hSTh105tpuDSy2ua3 08N2gpnORvldhPZEtcItNLZ9Y6qsTahz6Oka3smKvRvUCyoCLlMoAAAAAAAAAAAAAAAAABhz UcmFMgCm/wBkOVEdYGr3rOuCw+x88NHtFaKieRrIo6NrnOVeiIiFevshbOebTzMeyqFwpH+6 m+dxpNvLTovT6rTNSka2edjuuUTCoBtPGbvHpnVFsi05Z3OmnpZVV8qKitX3iWODPUFhXbuK 3xXSmSuXlzC6RObu8xTTZap0i/UPgurqeOaKrfyrLJ15FXvUsNr7RNj0JqfTV70ZU+DQ1LGK ix9EkRV7wLlJ1QHHtjlfbaV7ly50LFVf1HIAAAAAAAAAAAAAAAAAAADR97eb1N7pzfiLj4lK p/Y/VX1TtRIn4jvrFrN7lVdt7plMeIuPiUoXsPuVFtpctR3RGJJU1LHxwpnudkC6e/W7+ldC WmaiuUvb1M8TmpFE5MtXqnUqRwl6ks1PvZcrncayKkp6nLo3Su5U6uIm1BrCq1VrF991C91S 18nN2T16InmLK6A0Ltjrba+6361QQ010pKRzuyYnVqonsgLm0NXS1tM2po5454Xplr2LlFQ/ chPhDqa2Xb9Keqq31DYERrFd5EJsAAAAAAAAAAAAAAAAAAAAecnGn99qf4Y9Gzzk40/vtT/D AW94Ss+pJSZ/G/YS8RFwmfekpPf/AGEugAAAC9wAFSKplJPxc00ep3t7LsH9gk3se/pjJbKC NkbEbG1jY0ROVGoQ3xC7Nrrd8V+stS6hvlK1OxljTxlx5CLqGm4lrdT+CPhq6psXitmV6ZVE 7gLdYTzHxIxjk5XRo5F78pkqYlRxK5RvoZUr07+0Q/OdnErVwrTJT1VOkni9qj0y0D99QJb6 Xi7syaaWNJFik8KbF3I7PlRC2MeVjaru/CZIJ4etlanSlzm1VqmrfX3+odzrJInjMVe9CeAA AAAAAAAAAAAAAAAAAAAAAYc5GtVzlwiJlVMmnbw3ars+3t0rqTLZmM5Wqnu5Ajnc7iLsmnL2 +x2iiqbrWx+z8HbzonxHE0BxJ2q6XyK0agtdZaJJ/wCLkqY+zb/qdVwc6Isddpus1ZcIWVd0 nq5EdI/qqJk2bit0Hp64bX3C6rSxQV1IxOxnamFaB1m7HERDaby2xaOoZrxXK1Hc8DO0Yifq Nb05xJaitl2ji11p2so6SRyIkqU6tRP1nYcDOkrNFoKS/wA0LKi4rUOi7d3VeUlze7S9n1No G4UtxgiXkjy16phWqBtun7vQ3y0wXK3zNlgmYjmq1c4yc8r7wRXGrn0LdLfUPdLHR3B8UT1X 8FOiIWCAAHA1DcEtdlqq9W83Yxq7AGtbh7laV0RHz3m4RtlVOkKPTmX9RHruKLQCLjsq1fiI x2d0LBvFuDe9UayetbSUdW+GGmeq4RuehPybH7ZIiJ6WKbp7qgaf66LQHNy9lW/Eh2Fh4j9v 7tcY6Ht5aVZF5UfM5GtQ2D1D9sv7MU3xqa5uBw77f3bTlXDbbPFRVnZr2UrFXxV84Ew26rpa 2kZUUVQyohemWvY7KKhyCuPB1f7jAt90Vc6h9Stoquwhe5fwULHAAAAAABe4hjdXbHVWpdRe H2q9yUkPJjkSZWkznw7kR3NlObHnApRvboLW+laWgZNfXTtqHYXmmVfKbxY9mNe1lmoaqPUs jWSQNcjfCFTGUNg4vsup7Hy4Xx1z17upM2isJpa0Krm4SjYnf7gEDLsjuBlXJqaTP+IUeohr /kVF1NJ1/wCYUsk9zFYqczV9zJ8OcmEbhqp+l3AVwTZDcDkRHamk6f8AMKaPvZtTrOxbf1df cb++op2OTLFnVS5avajejmqvmyRHxafbNmq9Gq1V5m9M++B5qUTaqOqWema98kT1VOXyLnvJ y201hVXi3JT3bUVTRPp8Na3whWpgjrazWFn0lcLlJd7Ey7MqWqxjXLjkXPefpbtC6r1vcq25 6asEklLLKrmsa7CMRfIBs+uUn1drm1aaobnNXNlqGtbI6VX8qr5ckg7wWjWG01mt1BFqGZ9R MxEiibOq/wChpeyVsuG3W8dspNYWHlmqZmMi7R38Wue8lTjvt9cmrtOXyNOegjYiPlRekeVA 0K56P3BkprTdb/qt9LJcJWsgb4SreVV7lUlXZ3cjVOgddwaJ1rWNrKSrd9z1KOVyKieVFUjr czRl5v8APpqak1gtztlW+ONkiYRKd2Oq/qP011YnpuLpfR1uvq36vpk5XTtTCxYXqgF9YJmT MY9nVr2o5F86KfocOxRPgstFBJnnjgY12fOiHMA6HcT+gl7/AMFJ9VSAOBP+Rag+ET6Sf9xP 6CXv/BSfVUgDgT/kWoPhE+kCXt/LJPfNtrlS0yOWRsTnoje9einlpc6Koo62alqYnxTRvVHM emF7z2IkY2SNzHojmuTCovlKycTPDpT6pel60pTNgr0y6VrE/jFAjDgo0FcqS/VWsa+VlNRJ Rvja13Ryqqd/vEv8MEjJd09aOY9r0wzqi9O8qppy6biU+r49DS3+e3pzpTuRE7kzgvPsPtVB t1S1ErrktxraxjVmnVuFd5QJRAAAAAAAAAAAAAAAAAAAw7mx4uDJpu8t9rNPaErrhQIvhCMV rFTyLheoFZfsgj2MrrDO+dj42zrljV6oVd19RxwSUU8VRHMyaFHeK7PL7illbdsxcNy9Ax66 1zrySCDme9WSMykaIpWDW1FbbVqCpoLXcUuNJE9Wslx0cnnA5212i7nrPUtPb6BqtTnTnkVO jU8+S3u9lFFZYNF2V9VFNNRwRxu5XZyqKhUXSt01Tp61vudgrn0zHpiTl8xavh92vuevYrfr XVGppK/sGpyU7293lAtnaP5qpPgGfVQ5J8QRpFAyJvcxqNT9SH2AAAAAAAAAAAAAAAAAAMKq IqIvlA0LfrmXbO5s7aOJ6tXlVy46YU8yYbe2uZcVSeJj4ZHuVHL7Lr5C4O5jNU7nbyLoiG/S 2q2MR7X4TKOwQBxBbY6c23lbR2/VjbndFf8AboUbhWp5wIgo4ZZ6hsMLFfI5cImC5nDfoGt0 ptJqS+XaqiiWrt8jGwudhUynfgqHpyOrqLrGlA/s6pvVq+8TPssuvNy9UVGkK7VU9HAyHlkT l6K3uwBarhAcxdDy8jkd1TKp75OBpu0mg6XQOmYrPTT9urWoj5MY5l85uQAAAAAAAAAAAAAA AAAAAFVETK9EPNbjEcvqw18vatkjWbLcLnBcnip1TetNaKo0sU74KivqvB1kb3tRfKV217sT b4dHx6z1nr37pnj7TlkZ1coEvcHO4mm67RMFg8MZBXRr7CRyJze8WLPIGzXeq07qPw+z1j2r Ty5ikauOZEXoeh/CzvLDuNp3wOvcjbpSNRsiqvV6gTeAAAAXuUCNk3Vty7oR6ISCXwl8av58 dOhIlRUQ09M+onkbHExvM5zlwiIVcj/9XNP/AIZ/0kxcRdZV0ez98ko3OZJ4MvjN70AjvcHi Yt1vu81o0zaqy6VEDlY98MfO3Ke8avFxMathektbo26Mp0Xxl8FVOhuXCRozTsGg2Xl9PFUV 9SqSSyuTKoqk5VtsoKqn8HnooZInJhU5E7gNJ2f3a0/uJROWgV8FXF4ssEvRyL7xIhUmstdL oListMGnmJHT3CN8k8LF6KpbSJyuja5UwqoigfQAAAAAAAAAAAAAAAAAAAAAcDUFrp7xZ6i3 VTUdHMxWqn6jnnW6lu8Fjs09zqP4uFMqBUiKbcXYTUlXRUFvfc7HUSulakcayKnMuT6vep9y 98ZU0rBapbXaZuk75YljX4yVdPcR23d6r5KG51NPSPbIrE7RObK5Jc05crJc6RKmzTU0sK9e aNEQCo+l6/XPDrcvQOrt81zsL/HV8MayLzKc3cPfHU+4tCuk9G2CugSuwyWaaBW8v6y29wt9 HcIFhq6eOZi+RzUU4lrsFotcmaG3wxq7vVGoBpvD1oR2gtBx26ZUWpqHJNMv5yp1JHAAHEvF DHcrZPQy+wmYrVOWfMsjI41e9yNa3qqgU009qW/bCbj3OivVsqKmwV9Q6ZskMauxlemVJVbx R6F7NHOpLiiqnROzJYuVDprV9JJSVUUFdE12HphOimuv2d27YmV0/DhOuc9wGlpxRaDVM+C3 Hp3/AGs17XXFDZKjT1RR6WtdynukzFbEnZZRF8ncbVeLFsRaKp0FwZQQStXCtV6nM0ZDsm27 sXT77e6synLhc9f1gdHwiaKvFqtVz1RqOLs7heZkqEZjCtz5yfT5i7Ps07Ll5MdOXuPoAAAA AAL3EM7p6P3Lu2ofCdNXGngo+XHK+XC5JmMOVETC+XoBS3ebQe4lPRUk2prxSq1i/asTeXJu ll0BvNPZKKSlvFGkCwNWNO2X2OOhrfH/AKpWnkstrpXqx0b158L39SwWwF+j1Ftja5kcj1hg ZGq+6iARW3bre7HW80mfh1Ddu97uubzSfPqWVAFal263uymLzR+79vU0jfHRW6tt2/qqq+XS mlomuTna2VVUuYRHxbfebuHTPjJ+0DzUtNDLXXiCkYqc80vKme7OS6m321O6ds0zRvsdTbII Zokf7PC/rKd6Rx6bbflcJ4T3/rLxbu722/QG1lrt9tnbLd56REYjXdUTHUCvPEVT6mteqaCn u9xpJrtHMitfBJlWqSFNt9q3XuirfS3nVlm7GSJFRklWnaJ76FXq+7XvU+pnV8z5au41Enie Vc56ITlojh43HvthW+zV1VQ1CYdFCqr4wGyU/C1uC1Im0epolomKitRtSuG+6hLW1O3Wh9qa r0W1BfYKu9vXLnzTI5Wr7mSJI9KcS1uYlBR1la6mZ4rV5fIafrzbXUUDPRHcPVklBWPRXRxP Rcu+ID0Hs93tl2p0nttbBVRqmcxPR2PiOceZ+yu7F/251hBRR3KWptEkyNejlXHLnv6no9pa 8U1/sNJd6RyOhqY0e1UUDh7if0Evf+Ck+qpAHAn/ACLUHwifST/uJ/QS9/4KT6qkAcCf8i1B 8In0gWdMP9g73jJ8yKiNVM9VRQPOu6UfhvE+6Nzlby13NlF/OPRGkREpYvg2p/oefEvN66ST l/ra/WPQil/k0X6CfQB+gAAAAAAAAAAAAAAAAAAEdcQ6421rf/8AvIpIpq26enJdUaNrbVBJ 2cr2KrFx5cdAK26jt9/ruEqjSytmeje1WZkaKquTK+YpRUwywSLHPHJHKns2vTCopam67gbk 7Macg03e7VM6gWRyRSPxiRFVSOdJbc6l3d14ytjtUlDQ1L+0km5emMgaHp+muCaZr5+V/gqx +Kqp4v6i/PBpFybUQ5cuHI1e/u6EWcU2grNt/s1a7VaadsSoqpJIieyXykscHKI7aimRe7lb 9AE2p3AAAAAAAAAAAAAAAAAAAYVURyJjqpkAVi09zP4k69sSLzrHMjcefC4Kgb32vUVBr65O v8FQkjpnKySRq4VuVxhVLY7zaa1zofcpdwdNQS11KjXOlYxMcuSvu4uvdR7xytt0NifNcIZF 5laiZ94CK9JxVMt6jZSo9ZMLjl7ywnBoyRd661JVw9tOmfjJM4fNgKTTGjKnUmqKVJrnJAr4 mOTCw9O4jvhCTHEFfExlEVyJ7icwF9U7gE7gAAAAAAAAAAAAAAAAAAAEFcYyZ0tp/v8A50aQ 1xn2rUFdobSdTQQVElBDTL26Roqp+ssRxJ6KuutNG09PZnq2so5+3jREyrlROiFU9cb26009 al0PqWzyJ2TVjej8eMBWjHK7lcipjvQsfwH0tdLuI6el5/Bo3p2uO79ZDmitIXnX2rPArNRS L28uXqidI2qveejPD7tNa9tNNshhY19wmYnhE2OrlAk9vN15vP0MgAB5AAKk7qWvcLT29rNW aWtsdUrYnMTnYrk6qfF/3B3vvdnqrRX6conQVLOR+IF7i2z42u/BbnzqhjsW5XxWe54qAVl4 SKXcCx3artd9o0jtc71k6tVOVfIie4TJvPqi+aV0s+usFD4ZWLlGM5OZM+8d1q/VVg0jQLX3 yvgo4Wp3uTGSLPXM7byVqwS18PZNX+MciqgGpbBbfaw1DuAm5muUSOoRVWGDqnKi+TCloE6J hDpNHaksup7W242StiqqdyIqKzyHdgAAAAAAAAAAAAAAAAAAAAAA03ejHqc3PPdyfvNyNN3o Y6Tbm5tamV5P3gV54f8AaHSe4G2VXLdIEhq/DZESaNqc6dfOZvGw+4mi5/DtBaiqqmCHqkNR ULhU946Ph532s+i7R6Vq61Suqprg9qPzjvUuPZqyO4WuGrjZyslajkRQKrWLiC13pGrS3a/0 /KscfRZqeBXdPfJu2/3p0RrCJq0dxZTSKnWOocjHIv6zdL5YLReaR1NcaGGaN3flqZIT1/ww 6Tuz31WnHOs9a5c9ojlVM+8gE901RBUxpJTzMlYv4THZQ/QjvYTSN+0ZpKW0X+6LcZmzKscm MeL5CRAB1GrnPbpyvci4xEuFQ7c6jWX9Ga74JQIK4P6qrqavU/hVXLPy3F6NR7s4Q7bi31ve LBp+isOn38lfdnrC1+cK33lI54ZtxdF6RumpqfUd7gt877g9WpJnqh+nFHuJt9qGjs14sWpa WqrbZOsvZMRVV/uAdloThfobxZaW76rv9zlrqiNHyNSTKIq++fvrXhat1DZ6iu0rfbnDcYmK 6L7Zyoqp7xMOxetKDWuhKGvoJUcsMTWTNT8F2O4xvBufpnQViqZbrXRNquReygVer18wGi8J OtLndrTctM6gmWS42eZKdXquVdjy5J5Kz8GltrLjcdS6xqaV9LDcaztoGuT2TVLMAAAAAAA+ JnsjidJIqI1iZVfMfZ+VXC2opZYH+xkarV/WB5qcX2p0v271yhhkV9PTS4j69CxP2P8A1StV oypsUsiOkZMr0RV6oiHQcUO0OlLPcaC501MjamtkXtnKvsupOOxu1WmdG0FFd7LT9jNUUrVk 696qnVQJUY5HNyhkAARJxZ/eduH6SftJbIk4tERdnLgi/jJ+0DzNhbU+FvkpmyK6N6rzNT2P XvP3rKu53iqjZVVE1VIxOVnOueVDttK3ymtEF4hnp0ldVRqyNfxVyvU7HbGvslPUzNudOj53 55JFXu9wCY+Fi36A0/e4KrVTZpbjMqNjVzUWFq+TqX1t8lNLRRSUasWnc1FjVndj3CjVvvOj V2l9Ao7G+TUM73JTK13jNcvcpbPYmjutDthZqa8Od4Qynaitd3t9xQN5Km7rzM0tvdFftcW6 qu1icr1ijbEsrWp5OhbHmTm5c9Tr71aLdd4fBrhRx1Ea/jNToB5ub8U9BfbrPqvTdpmt1lci tjbJF2a83vFyuGa909q4f7Vc7rVclPBT5c97u40bjttlDatpqSmoKeOCJKjua3HkPjTGnLnq vg4gs9oR7qp9O1WsZ3uwuQNzrt+dEarsl/s1FJVQzMpJWpJOzlY9cKnRfKatwKJiiv8A5U50 6/rIQu9ov2pNFLpeh0dV2ystadrUVqr7NrU6k2cBiKy0XqJy5VitRV/WBZ8+ZMcq+fCn0fMj UVqr5URQPPdf/VLL/i1+segtLzdhHnGORuPiPPlW54pZeZc/da/WPQalVPB40z1RifQB+oAA AAAAAAAAAAAAAAAAAGHNRyYUCmf2Q587qmxRvVVh7dcIWL4fqOjh2xsssFLFE9aVmXNbhV6F evsh2c2BUXGJ1LF7BKq7WWRV/qrPoAiXj9x6ndDn212DaODrKbT0/LjPK3v941jj9RF27ocr j7a42fg867TU/TPit6ATcncAncAAAAAAAAAAAAAAAAAAAA0TfTt27Z3Xwd3jqxfL7ilUeAOn gn3K1B29PHM5GOXx0zjxu9C2W9zUbtvdMeWNfoUqn9j+RPVL1Evd4juv+YC5urWo3TNa1qIi JC7CfqUpBwgt/wDMFfkz5XfWLwau/o3XfAu+hSjvCH/6gr71z4zvrAX2a5FVU69DIQAAAAAA AAAAAAAAAAAAAAPNzjLbL6sNasiqrXTeKekZ5x8aSou7c6J7cBarg907Z6LbOnr4aGBKt7vG m5E5u7zk5EQ8JyKu0dJhceMn0EvAAAAAAEB7m703/QOuI6O5WWWeyOTLp4oVcqdfOSNoDc3S WtqRlRa7lEx6pnspXo1/xGzXyy2y9UMlFcqSOeGRMORzU+kgHX3DbBDXOve31xdZKyNedGIq uRygaZqe1VW8HEL6AXOtnisdFztfGx3s1avTp5Sbl2I29S1Lb3WiBUc3k7Tsk5vfKqW2r3O2 j3MbqXUdpqq+nTLZJUbhHovlJ69dTo1LT4U6NfCEbnsMrlV8wGk7e0tx2n4hqfSEVZLLZbij 5I43Ozyond0LctVHNRydypkqXs9R6i3S3qj3DuVBNSWqj5mU7Hp3tXuLatRGtRE7kTAAAAAA AAAAAAAAAAAAAAAAAPwrqWCtpn01TG2SJ/RzVTop+4A05NsdDpVNqfS7Qds13Oj+yTKL5zba aGKngbDCxGRtTCInch+gAAAAAAB+dRDHPA+GVqOY9MKin6ACM7hsnoCsrpamos1M6WVyvcqx J1U/GPYrbxU5m2Sl+aQlIAdFo3Sln0nQPorNSx08L3czmsbjKmva52o01rC+Q3S9RrO6JyOS NzUVq4N+AHCstqoLPQR0VupY6aCNMNYxuEOaAAAAAAAAucLjvAAhviT0ffNVQWlLRCyR0Dsy cy93UlDStLLSact1PP0lhpmMeid2UQ/HV2prJpe1vuN7rYaWBiZzIveQvV8U2hqeuWmhas0X NjtWu6e+BYIGqbea90zrS3JUWK4wTuRMvja7Ks982sARJxapnZy4JnHjJ+0lsiTi1VU2cuCo mfGT9oHmYyB01Z2bcZfIqJ8Z2V6sF1sPYPrqaSJk7eeKTlXCp75wqPl9E41RfG7br8Z6GTbU 2bcnYqzQVMMbK9lE3sZse53AV84Ud1dNW6709j1baaKXmcjaerexFejl86+QvbPebXSWJbr2 8fgTGcyPaqYweVW5OiL1oHUk9tudPLErHfapcYz16YJP213uuD9CVGgtQTSPjmx4NUK7CRon kUCzLeJnTrtTeBtoK70PWTs/CewXlznr17idLRc6S6WqC5Ub+0p52o5jk8qFL7Lf7vdNufU9 odDVNRNPI7luLWphEd3LklHUW5dBststbLHV1Lam+QUvZpCjvGRQNd+yB6itS6NpbK2oa6t7 bmVjVyqIdFtBxEaR0JtXZrPM6WSsjiRsjeXKIuSqeudU3rWmoprvdZnzzzOVGN8yZ6ISrofh 11DfduqvVlW9aVkbEfBE9vWRPcAubZ9W6Y1ttTe7/p2KJjpKKRsqo1EdnlXJG3An/ItQfCJ9 JEnCJepaKm1dpmpqeWOK3z4Yq/hYUlvgT/keoE8qSJ9IFnT5kciIqeVUU+jD/YO94Dz1enNx Sy9f+LX6x6D0qJ4PGvl5E+g8+Fw3ill8matfrHoPS/yaL9BPoA/QAAAAAAAAAAAAAAAAAADD nI1MqZAFN/sh2f4Bx3duuSxewqr6lVk5e/wVn0Fc/sh6qkmn08izqWO2ERE2ssmEx9ys+gCJ OP1FXbuh9yVxtPB1n1J6fl7+Vv0Gr8fqZ27oeuPtrjaODlUTaimVVwnK36AJtTuAAAAAAAAA AAAAAAAAAAAAaRvbzepvdOb8RcfEpVP7H6qJuZqJO9eR31i1m9njbcXTPi+Iv0KVT+x+r/4m aiRE68jsr/mAuZq3m9LlfzJ07F2PiUpDwg4XiCvuE8rvrF39WuRdN1+F7oXfQpSDhC68Qd9y 38J31gL6N5srlEx5DITuAAAAAAAAAAAAAAAAAAAADzk40kT1Wp/hj0bPOTjT++1P8MBb7hM+ 9JSe/wDsJdIh4SlztJSZTHjfsJeAAAAAAAAA4N3tFsu0HY3Ohgq48Y5ZW5Q0/wBR/b/wtKhd OUCqjs47FMG/ADiWq2UFqpUpbdSRUsKdzI24Q5YAAAAAAAAAAAAAAAAAAAAAAAAAAeQDyAQ3 e9e3am35ZpaNjfAlpmvznrlSZG9URSt+pl/810aInXwNv0lj2+xT3gMgAAAABGm92v6zRNRY o6SBkvohUrE/m8iElkAcW6Klw0g7vRa1U94Cc7JVOrbTTVb0w6WNHKhzDqtJ83pct65THYNy dqAAAAAAAABBu+m5GsNvb9SVdFaErrO9VWociK5zE9xENj2x3r0brqOOKlrVpazCc8U/2vr5 upI9dRU1ZGsVTBDNGqYVHsRSD9zuHDTd8mdddOvfabtzczZGyKjM+8gGib0sqdyN97Xoqatd HZ4puWZI3ZR6ftJqt2ye3NBbW0a6dopURnJ2jok5l90qdetK7sbaa/otR1kU15joZOZZYY+i oTbQcVWn1taSV1lq4qxjcPiVcKrvcA0zUGnHbNb9WOaxVL47XeqnkkpmrhqInuFvKSZKimjm b3PaioU/0s7VG9+8tDqapttRb7Bapu0gZM32Se+XBgjbDC2JnRrUwgH2RLxZfeduH6SftJaI l4s/vO3D9JP2geZ9EieirF657b9p6rbH/etsX+Eb9B5UU/N4e3kcnN2vT4z1R2JZIu1FiSZ3 MvgrO73gOs362ntO4+mZ4XwMZcmMVYJURMq7yIqnm/r/AEZedFakms91idFNFJiN3kXC9+T1 tKW/ZAqnT81wt9PTuhfdGxqiqxUy1c+UCB9M7m620xAlupayR0j0wyTn6tTyGpazueoL1d/C b7WS1lS9fF53c2Mm/bb1+hqbTNfSaptc8t7WFfBZOfGHeToadpl0EeuqN96YraXtk9l5s9AL D8JnD/JepIdVapp+SiaqLDC5PZKnuKXMu1rp26XnttHAyKBsKtZGxMIiYU+NETUE+mLfJa3x OpfB2I3s8Yzg7efCxPaq9VaoHnJtekli3W1fSzIje0gnRM+ZVUsJwNoxItRIz8dvX9ZXPeis XSm890dGnN4RG5F5fdUsRwHv7W13ub8dWr/qBZ4+ZEy1Vz3Ip9HxIjsLhemFyB57yIvrpJMJ n7rX6x6D0v8AJov0E+g8+HovrpZMLj7rX6x6DUqO7CPK9ORuPiA/UAAAAAAAAAAAAAAAAAAA DDmo5MKBTj7Ie7lfp/pn7epYvYZXepXZFRMr4Kz6Cuf2Q5y9pp9Gr/v1yWO2E+9ZZOufuVn0 ARJx+onqd0OfbXG0cHf3p6foi+K3vNX4/VVNu6HHllcbRwdoi7T06O7uVoE3J3AJ3AAAAAAA AAAAAAAAAAAAANI3ucjtt7pjyMVP9FKp/Y/Ou5mo07vEd9YtZvcqLtvdMe1r9ClUvsfyJ6pm olX8R31gLmasVq6cuGE6pE7PxKUi4Qn/APmDvqp5Vd9YvBq7HpbrvgXfQpR7hDT/AMwd9yv4 TvrAX1a3CquVXJkJ3AAAAAAAAAAAAAAAAAAAAB5x8aWfVbnynTtuh6OHnJxp/fam+GAt7wnZ 9SOk5eq8yfQS8RFwmfekpPf/AGEugAAAAAAAAQrxC6yvmmrzaoLU5EjnexH+NjvdgmO3PdJb 6eR/snxNcvvqhXriwRvphsbubDu0Z0/zFg7T/NdJ8Az6oHJAAAAAAAAAAAAAAAAAAAAAAAAA AAL3AL3AVv1Mi+usjx/U29f1ljmK7uVOmEwVx1MiLxWR9cL4Gz6Sx7fYp7wGQAAAAAgHi1R3 h+kfKnhq9CfiAOLhFWt0grV6+GrlAJr0l/Rqg+AadodXpH+jNv8AgGnaAAAAAAAAAFVETKqi InlU4jrjbe07N1dS86fgrK3P0kGcT+5l6stVQaO0o1XXa6Za16JnkI/peHTcivpG3io1cjLh I3teXtHIiKvXGALbVdPS11I6KaKOoicnsV6opq8u2Og5qjwiXS9vdIvVVWPylftDbs602x1G zSe5VPLNQq7kgrkZyx486qpaKwXi33y2x3C2VUdRTyIio5i5QD4ttDZrJEyjooaaiY7oyNuG 5947IrrxF3Gup95NA01PUyRxS1ao9rXKiO98sNSZ8Gjz+KgH6EScWqZ2cuCZx4yftJbIk4tV xs5cOmfGT9oHmjRovonH0THbd/6z1T2NVfUtsfMmPuVv0HlN2z46pXN72yKqfGXIpuJW2aZ2 XoLXbW895jpmx5RUVGrjzAS/xH7z2nb6w1NLT1TX3aZitiY1c8q+RTzt1LqS66n1BJdLrUST 1Er8oirnGfIh9at1Hd9V32W6Xad9RUzO8Vue79RYfhZ4e5dQTM1Rqyney3x/bGQqmFf5UwBG +i9i9xtZW917pKHlha3Mb5Hcqrju6KaFrWy37T11fbb9TyRVMLsZci96eZSxO/W/Or9K66dp /S6wW+20LWpHEsfVcdOpIlDpah4h9pI7rc6FtNqKnhTkqUbytkX9oEQ8K+/dbpK7RWPUVXJN bJVRjHPXPIql+bNcqG822K4UEzJoJmZa5Fz0U8n9wdG3jRuoJrVd6eSnljcvI9yYRUz0VCc+ E3fubSlezTOo53S0ErkbFK53SNPdVQOr477bDbt4Gup0RnaU7XLj3Sa/sfyqum7qq/mENceF fR3PdCjrKGdk0MlExWuauUJl+x/pjTd1TOfYAWkPiRXYVETphcn2Yf7B3vAeez1ROKWXP9bX 6x6DUv8AJov0E+g891ei8UsvTP3Wv1j0Ipf5NF+gn0AfoAAAAAAAAAAAAAAAAAABhyuRPFTJ kAU3+yGovNYeVE6zrksZsGmNrLIn/Ks+grn9kPVUWwYXH29SxmwSY2rsn+FZ9AETcfq427oe mftrjaODhEXaimRevit+g1fj9x6ndDn21xs/B3lNp6fConit6qBNwCdwAAAAAAAAAAAAAAAA AAADR97EX1N7plETxF+hSqf2P3Hqnaiz+I76xa3e9UXbe6YX/dr9ClU/sfn3y9ReTxHfWAuZ q1XLpyvymPtLsfEpSHhCTHEFfU7+rvrF4NXdNN13wLvoUo/whNROIO/Jnyu+sBfVO4GGuyqp hUwZAAAAAAAAAAAAAAAAAAAAecnGn99qb4Y9Gzzk40lT1W5/hgLfcJn3pKT3/wBhLpEPCdn1 I6TlXC8yfQS8AAAAAAAABXLiwjzqKxyZ7pGfWLCWn+a6T4Bn1SvfFgiemOxrnr2jPrFhLT/N dJ8Az6oHJAAAAAAAAAAAAAAAAAAAAAAAAAAAeQBe4Ct2qW/+a6NU6p4Gz6SyDPYp7xXDUqL6 61jspjwNv0lj2+xT3gMgAAAABX/i363HSCZxitXqWAIA4uG81dpDrjFaoE16S/o1b+uftDTt Dq9IpjTNvT+4adoAAAAAAAABU7iAlXSW/wDpjU11a70NWRyrJjKNLPacvdtvVthq7dVRTRyM RycrkVcKdPuZoKxa9sUlrvcHOxUw17ejm+8ppeyW0Eu3V4qJYrnNUUbmq2OOSVXcqeQDeNxN D2HW9lkt16o4pstVI5HNyrF86FYq2PcLh81IlTTOqLxpKSTDmvVcRIq+RE8yFxDhXW1UN0oJ aKvp46iGVqo5r257wKmbk6+sGu90dublZKntV8KVZGKmFapbuk60sa/moV5Thot1u3ToNV2S o7Glppu0WF7u73kLEwt5Ims8yYA+iJeLL7ztw/ST9pLREvFn9524fpJ+0DzTt9OyprZo3JJn mXHI3PlO01TYaO0w0ng1U6omqGo5zVTq1fMbLslqq16XvtfJcbb4etSnJE1GI7lXPedZVyRS 7nMrLnC+Kknq2vax3TlbzATbwnbB1OpLmzU2p6Z0Vuiw+FipntFTyKheu30VLQUMdFSQsip4 28rGNToiHWaFdbHaVoHWhYlpVgZhY+7OEyd2BDm5/D5pPXGo2XqqRKeZFTnRjM86J5FJJ0Zp q2aVsUFptdOyKGFqN8VMZO6AEVcQO0Fn3I09OroWx3SNirDKjfGcqJ0ap5wa30ldtH6hntN0 hfDUQvw3PlPXQpz9kEpNOtS2Tt7JtzXPRmMqufKBUOvrrxc5WOr31FUrGoxquRVwidxd/gAa rNOXZruipyHF2N2+sdXsLcb3dLWnh6Ur1Y9zE7kblFOw4EulDf0TuR6InxgWdMP9g73jJh/s He8B56u8Xill5U/4tfrHoPS/yaL9BPoPPZ7XLxSSpn/i1+sehNL/ACaL9BPoA/QAAAAAAAAA AAAAAAAAAAABTb7Igqc+n0VO+devmLG7B/essnm8FZ9BXP7Icqc1gavlnUsbsH02ssif8qz6 AIk4/MLt7RJnqkjlNo4O+u01PhM+K3oavx+pnbyhXOPtrjaeDrPqT0/L38rfoAm1O4BO4AAA AAAAAAAAAAAAAAAABo+9vL6m905fxFz8SlVfsf3XcrUWe7ld9YtZvf8Ae3ufwa/QpVL7H7lN zNRKn4jvrAXM1arvS3X5TCdi7HxKUf4Q/wD1BX3y+M76xeDVrs6br0wqYhd9ClIeEFc8Qd9x 06u+sBfVO4GG82VyqY8hkAAAAAAAAAAAAAAAAAAAB5ycaSIm7c+E/wB8ejZ5x8aK53bnTHdM Bb/hM+9JSe/+wl0iLhM+9JSe/wDsJdAAAAAAABhy4aq4zgCufFgzOo7G/PdIz6xYS0/zXSfA M+qV74r3f7Q2JML1kj+sWEtP810nwDPqgckAAAAAAAAAAAAAAAAAAAAAAAAAAB5AF7gK3am/ 9V8aKuE8DZ9JZBvsU94rfqbl9dbHlFz4Gz6Sx8bs9ML0RAPoAAAAAIA4uMeHaQXPVK1c+8T+ QDxbcvh+kc961qgTVpHrpm3/AADTtDq9Jf0at+PaGnaAAAAAAAAAFVETKqiJ7oRUVMouTotf W+6XPSlZR2adsFc9v2p7lwiKhAGnN/avRkVVpnX1LM++Ruc2m7NuEkTub74Fm0ciqqJ3oZKz 0+5G892a6utloigo3dWMmp15sHd6A30q4722w68ts1uq3uwyofHyRKvm6gT6D4gljnhbLE9H scmUci9FPsARJxaKibOXBV/GT9pLZEnFn95y4fpJ+0DzNgnqIK5z6V6sk51wqe+dndbrNc4m NrWqlTEmGvXvU4NEjW3SNyYVe26p+stbuVsJDftorRq3TcCpcGUjXSsansvOuAOv4Rt+pbJP FpHUU6rSPVGwyvd3Kql5KKqp6qlinp5UljkblrkXvQ8hpaWqgqXQStfTVsLsY7nZQtdwr8Qa UbIdIawmVqMxHBM5cYT3VUC6QPxoqmCspY6mmlbLE9qK1zVyioaBvVupp/bqwzVldUtfVo1e zga7xlX3gPrevc6y7dacnrq6qYlU5ipBFnqrvIeb24OubnrXV0t+vMj5GLIrooHLlGJ5kP03 S17etwNRz3i8VDliVy9lFnxUbnp085tnD3s7d9yNRwyVNNJDZ43J2kjmqnMnuKBytLb/AOpb Vbp7K/n9DpqZYEhVcImUxksbwIPbLa73M3ue5q/6lf8AjF0XaNE62o7VZouSFtKxV86qTz9j +z6W7rn8wC0h8yORGqnlVFPo+Xp4jveA89Zc+ukk5f62v1j0Ipf5NF+gn0HnwrE9dLKmV/la /WPQelVPB408vIn0AfoAAAAAAAAAAAAAAAAAABhyKqdFwZAFN/sh2OawIvf264LF7C4ZtXZO Zf8AhWfQV0+yHoiusCqvVJ1wWM2ETO1dkz/VWfQBEvH7hdu6HK/71xtPByqN2oplXu5W/Qat x+49Tuhz7a7BtHB01HbT07V7uVv0ATcAnRMAAAAAAAAAAAAAAAAAAAANI3s8Xbi6Z8bxF+hS qf2P1P8AxN1EucJyO+sWs3tdzbb3ToqYYqf6KVT+x/ffL1Fnu5XY+UBc7V39G674F30KUf4Q srxBX3KeV31i72rXZ03XphekLvoUpBwhuX1wV9x08Z31gL7IDDWoiqvXqZAAAAAAAAAAAAAA AAAAAAecnGn99qf4U9Gzzj40s+q3Pnu7boBb3hMavqR0ic34X7CXyIeE7m9SOk5e/mT6CXgA AAAAAAAK6cWH9ILH8JH9YsFaf5rpPgGfVK98WDVXUdjdzJhJGdP8xYS0/wA10nwDPqgckAAA AAAAAAAAAAAAAAAAAAAAAAAAvcB5AK36mcicVsbVTP3Gz6Sx7fYp7xW/VGF4ro+nXwNn0lkG exT3gMgAAAAPmR7Y2K964anepXbixulumrtJKyrjdyVqqqI5OhPmooFqbHWwNcrXugejVReq LhTyy3YqL5bNbV9ur7hVyugkVzEfIq8uV8gHqDomtpanTdAkE7JPtLe5cndlcOBOguiaCqq+ 71VRO+SVOx7R6qiNwWPAAAAAAAAA41zq4aKgmqp3oyONiqqlRLLt9W703y86yqqpY6q3zyRU K471aviltr3b47haqqkkVeWVip/oV74Zb4zTOrL1oW7qlJUvqpJ4O18VHNVemMgdtspubXUN yXQGu2eCXenXs4ZpE/j/ANhvO9+g7TrHR9TJURsSrpInTwTNTqjmoqocbera2k1xavCqTFJf KdOamqI/FVXe6pF2n95KzTWl7po7X8MsV5ggkhpX8uElREVE7+/IG98LGp6y76IS03ORZa6g VWyPcvVUzhCYiDuEaxVlLpCS/wBex0U1xVV5HJhUTPQnEARJxaqqbOXDCZ8ZP2ktkScWufUc uHL38yftA80KJE9FWLnr2vd+s9U9lWo7aixtViPa6kaiovlTB5W0bkW5xtx1Sb9p6qbHKi7W 2L/Ct+gCtfGRsq2lk9O+mqbCtXmqIo2+xRO9SuVp0zJrG3Oq7KitutN306dFeqeU9SrtbKW6 UE9FWRpJDOzkc1yZTB55X+lft5xEVqWbCsV8iMhTu97ADQnEVrnQlrl09Xslq5I0VjOd2FZ5 CMtydT6k1Zd1vOop5ZO0VXQscvREJOorVpO/S3q5a2gqaLUCQufSQRpyte78Hp5SLWtqLnqS 3267xrSQNkRrUenKuM+UDeOHTZ66bk6gjqKiF8NnhcjnyKnR+F6oei2idMWnSthgtVop2Qwx MRvipjJwNq9PWbT+jLfTWaGJsToGOc5iJ4yqiZNrRERMIBQ37IO1qbiUz0TxvB2dSTvsf6qu m7qq9/iEZ/ZBVxuHTKvtDCTeAFUdp27Knd4gFoz4kVeVUROmF6n2Yf7B3vAeernf+aWXlTP3 Wv1j0GpUTweNcdVYn0Hny9UbxSydP+LX6x6DUvN2Efdjkbj4gP1AAAAAAAAAAAAAAAAAAAw5 VROiZMgCm/2Q/wBlYFRM/b1/UWL2EdjauyK5f+FZ9BXT7Iei81gVO5J1LG7C4dtXZMp/wrPo AiTj9RV27oVT21xtPB0qptPTKiZXlb9Bq/H25U29okXuWRxtHBx02ops/it+gCbU7gAAAAAA AAAAAAAAAAAAAAGkb2rz7cXRG9cRr9ClUvsf2E3M1F5V5HfWLW73Y9Te6Y9rX6FKp/Y/MJuZ qJV8rHfWAudq7+jdd8C76FKPcIaf+YO+5X8J31i7+rERNOV+FzmF30KUh4QkxxBX1E87+/8A SAvqncAip5wAAAAAAAAAAAAAAAAAAAA85ONP77U3wx6NnnJxp/fam+GAt9wmfekpPf8A2Euk RcJn3pKT3/2EugAAAAAAAAVz4sEZ6YbHlfH7RmPlFg7T/NdJ8Az6pXviwYi6isbvKkjPrFhL T/NdJ8Az6oHJAAAAAAAAAAAAAAAAAAAAAAAAAAAL3AeQCt+pf/VbH5PuNvX9ZY9vsU94rhqX pxXMVe7wNvT9ZY6NuOuV6ogH0AAAB1Orb7T6csVTdqqKWWOBvMrY25coHaOY12cpnKYPPfjM 0Y+m3iWppmq1lxe1jURPKWXXiT0yjseg14x/h1Ik3q3C09rXUmnbnFY7py0FT2k2adeqAWT2 LsbbJthZ6VjeR7qZiv6eXBvaECUHEVpejt8NLFZLwiRMRqJ4Op+7OJTTfe+y3jH+HUCdAQWv Eppnm6Wa84/w6hOJPTeE/gW89/8AV1AnQEF+uT02j+tlvHL/AIdTK8SemuZf4FvPufc6gTmC DE4lNM48ay3nP+HU+V4k9Ocv8y3jP+HUCdSKd5do6fV1Q2/Wip9Db9TpmOpYnVcdyHReuT01 yfzLeeb/AA6mI+JPTir41lvGPcp1A1yl1Dvrp+B1tqbFV3l6+K2ryiY906O57Ia33JrH6k1d XyUldAxXU8Lm9cp1RDf/AFymmlziy3j3PudT69cnpnl/mW85/wAOoH6cPOqb/HLPojU1qkp6 q2eK2d3+8Jta5HZwvcQIziF0c2pWrTTdzSd/s5PBV5l/Wcr1yel0ziy3lM/8uoE5EScWiomz lwVfxk/adKvEnpzCIllvGf8ADqaBxA75WHU22tXaqW1XSKWRyeNLAqNQClVH/Ocfi/77v/We qex/KzayxL3ZpWnlPBPyVjZFTxWyc3+pd3S3EzpbTG1tBb5Kep8PgpkYxFZ0VcATLv3uradu NLy1M9Qzw6Vqtgjz15vIVL4edN3jdPdup1zeEc22xSufM96dG+Uj3UOob5ulrtt51DT18tqd L1bAxVa1ufJ7uCX9zd2dP6c2ni0Zoe219skkY1stQ+Ls3Px3rkCUdwtUcP8AT6tpZrvFR1dy hc2N0qKqcmOmehHXE3traNWWWLXW3U0dTBTN5pI4U7/MpB3JpJ1PakrWXGWrqahPDJZGZyxe /lXzkobL6so9GbtQWCmkrKvTNwVUWCfqqJ3J0A2vhI38mhqWaM1bMrFZ4kU0i469yNLkxTRS xsfG9rmvTLVRc5Kb8UWwTmIuuNDxvidjtXxR9FanflETyjhO3+nirKfROsJXMkRezhmm6KmP xlUDXPsg/wDT+mXl/wBwzqSX9j/VF03dVRMJ4hF/H/PHNuBSOhkbIx1OxUVFyiko8AP9HLtn H4HcBaM+JEXlVc9ML0Ps+XqnI73lA898qvFLLlMfda/WPQal/k0X6CfQefD8pxSyYx/K1+se g9L/ACaL9BPoA/QAAAAAAAAAAAAAAAAAADDlRvepkKiL3gU3+yH55rBju7dcljNg1ztZZMJj 7lZ9BXP7Ie5Ufp9PIs65LF7DZ9SuycmP5Kzv94CJuP1UTbuhymftrjaeDlEdtRTIvdyt+g1f j8VU27oemftrjaODrPqT0/L38rfoAm0BO4AAAAAAAAAAAAAAAAAAABpO9jWptxdPJmNfoUql 9j9x6pmokxleR3X/ADFqt68epvdcZ9gvf7ylVfsfmfVN1Hj8R31gLmauaiabr1Tywu+hSkPC EipxBX3PXq76xd7VvN6W6/mxjsXY+JSkPCC1E4gr8mfK76wF9GtRFVUTqpkw1yKqp16GQAAA AAAAAAAAAAAAAAAAHnJxp/fam+GPRs85ONP77U3wwFveE5FXaOkwuPGT6CXiIuEz70lJ7/7C XQAAAAAAAAK48WD8aksTMd8jPrFhbT/NdJ8Az6pXziwRPTBY1/vI/rFg7T/NdJ8Az6oHJAAA AAAAAAAAAAAAAAAAAAAAAAAAeQBe4Ct2pseuujVf6mzp+ssgz2Ke8Vw1M5E4rI0xlfA2/SWO jVfLjGEwB9AAAfjWUsFXA6CojSSNyYVF8p+wA6H0n6d/JsPyUCaQ08iKiW2Hr+ah3wA6FdH6 eXvtsPyUHpQ09jHobDj9FDvgB0PpO07+TYfkoZTSGnkRE9DYen5qHegDonaQ087vtsPyUC6Q 08q59DYc/ood6AOhXR+nVXK22H5KGV0hp5Vz6Gw5/RQ70AdF6UNPdf4Nh6/moG6R0+iYS2w4 /RQ70AdCmj9PIuUtsPyUM+lDT2MehsPyUO9AHRLpDT2MehsOE/NQLpDTy4zbYen5qHegDovS hp7m5vQ2HP6KEV8U+nbLRbRV81PQxRvR6Ycie+TiRJxZoi7O3DP4yftA8ykVrKl71X2L16ef qSztJtzf9zLvTy1rXUtjo25lqnJ4rWp1waDorTFVqvVEdno5YYpZpeVqyu5W9/nLZ7dS3mr2 /ve2VO2jpLpSZa2aldhJGtTrlUA2LS+5OyemJ4dKW6GkdDEqRunzlFf3KbTvztXZtwttPC9M U8fhasSSmkjTvTvPP6stNfTX6a0y07o61Z3NRzkx1z35PSHh4bLZ9rbXSXi70qz9i3CLOmWo BRvVTr9ZKS12S+aamgq6OryyVyfx2O5EJv4c9tLrdNXJuBrChdbaClXmp45e5zV8pvvFu2yz O0fLAtBJIt1aj3tciqqe77hzuJ+7T0OwM3oHcaeNzI2o5IJU5k97AEm024Wg7pU+glPfKOaV y9msKLnPkwVk4r9gqimrX6x0ZTOR2e0mjiTrkrBpW51sWobbVUlwqG1rqhvMqux5fKehGqdx I9J7DMvNZPSVtw8Ha1YnvR3Mq9OoHntrXVF91BNFDfZHyVFM1Ik5k6oidMFy/sfyKmm7qi9/ iEAX7TldZqKfcPUEFqfS3TLYYIXI5Wq7qi48hYXgNe2S0XqRmEa5WqiJ5OoFnj5kaitVfKiK fR8yOREVPOigeer2KvFJKir/AMWv1j0Ipf5NF+gn0HnvKiu4pJOVf+LX6x6EUv8AJov0E+gD 9AAAAAAAAAAAAAAAAAAAAMObzJjKoBTj7Ie7DrA3zzr1LG7B49SyyIi5+5WfQVy+yHK3msDf Ks64LF7DcybVWRG4z4Kz6AIm4/VVNu6HHllcbRwd9NpqfrjxW9TWOPtEXbqiyvdK42fg6VE2 np1VMpyt+gCbk7gE7gAAAAAAAAAAAAAAAAAAAGk73/e3ufwa/QpVL7H6ieqZqJe9eR31i1m9 jP8Aw4uiIucsVevvKVT+x+ZTc7UeMewd9YC52rv6N13wLvoUo7wh/wDqCvvXPjO+sXg1bzel yv5sY7F2PiUpDwg9eIK+4RO931gL6oAncAAAAAAAAAAAAAAAAAAAAwqLlMLjr1POXjT++1N8 MejZ5ycaf32p/hQLfcJn3pKT3/2EukQcJjP/AAjpEyvsv2EvgAAAAAAw5FVqoi4UyAK48WGf THYk5v8AeR9P8xYW0/zXSfAM+qV84sMemGx92e0Z9YsHaf5rpPgGfVA5IAAAAAAAAAAAAAAA AAAAAAAAAAADyAeQCt+p0xxXRq1c/cbPpLHMaiJnyqhXHUfTixZ/gm/SWPb7FPeAyAAAAAAA AAAAAAAAAAAAAAAAAAABFPFXTyVG0Fwji9llF+klYjXiU+9Tce/u8nvKB587I6GuGt9Xy0Ft uKUFTG7LJfMuSatf7cas2W09JfqXVcUtwnkRqpy9XK7oaBwoahtemde192u03ZU0K8zl8uMq S/vnu/obczTlTY4vDIZmSo+mnWJUauFynjAaxpnh/wBwNfUMeqbpeoqWpn8ZqLFhU8ymyx8N m50bEYzW6I1O5ERTWts979w46iLRtLDQOfDhIJZJcI/yJlSZaG68QiPSSay2l8TurXMmyioB XXiA2t1toKy0N0v2pfDoXTcsfRU5Xec1HTVi3Y1vapYrTTVlxoG9HK3KtUl3ism3Vv1ntFm1 NaaKngqKpGU7on5Vz18598Pu4t12auKaV1rb/BqGpemJ2tVcebqBEEWxG6tPO2eLTNakiOyi 8vcp2l+2z3sqrU6G4Wi4SUsaexVFxhD0bsV3ob1RR11uqYp6eRqOa5jkXvOZOztGOjVqKxzV RcgeV+jbTe9U1dbpuvrnwtoYXSJHIq9HN8hangDhko6bUFFLUtkfE5qK1PJ1IZ4k7NUbe71y utzeyhro8uc3p7JSQeBO9spdbajoJZOZ9W9vLlQLoGH+wd7xkw/+Ld7wHm9qq7wWTiSkrppU jibXfbHr3NTm6qXAg4gdApqOls0NyhlZIjW+Eo7xc4KQb0W9tx3rr6SSRI4n1bu0fnGG83VS w23to2OuOlk0BSVaOvEjOVK6RiI9rl8qOAtvSVENVTR1NPI2SGRqOY9q9HIvlP0Ky7b61vm1 GqG6G1u989pld9wVyqrvE7m5XuLLU08NTAyeCRskb0RWuauUVAP0AAAAAAAAAAAAAAABhyqj VVEyR1ubu/pjQ1VDR187JKqRU+1I7qiec6zfTdeDSNJ6D2dvhl+qvEp4WJzYd+djuItsFh0r pOim1bvDVtq7ncWq5lPIqP7JrvMi92AI140Neae1lPY32SuiqFjm5no1fYlqdkr1Z6fbGyxu ucLX+Cs5kVe7oUG34s+kqe9Nu+jq581BVP8AFY7orf1GuUFx1xHRsSirLw2nRMMRjXYwBcbj uutsrNvqKOnrIpX9o5cNXJ1PDhvLpPSO1KQ3GujWsjVrW0+fGVPKpUTUdXqmalal7qblJFnx EnRcf6k08ONr2y00xmpte1KVEr28kVKrUexUd5VQC8W3WubHrezNuNnqo5EX2TEXqhtBUy52 +fRVwZuNtlULV6fmdmqo2u8WNidVVGp5Sw+2OurTrjT0Nyt8qdorU7WJejmL5sAbYAAAAAAA AAAAAAAAAdPq7Udr0xZZrrdalkEETVdly4zgzq7UVt0zZZ7pc52xQxNVeq9VXzFZ83nefUcl +vM0lt0ZQO52NcvL22F6o5F8gGwa9330dqbbi8QwV0dPUIvJCxzusqYXqhEXAJXUFPuFf56q qjhR0aq1XLjPU5PEFBs5qSyrBpGoSiu1tb2TY4mI2OXHeqqVlsNRfKavmSyS1cUqeK5aZFVV T3cAeqmqNQ2SXT9cxLlBnsXfhe4pRfhw1VZNM743q4XasjgpnvcjZHL0XxiLZbjr5Yn9pW3v k/Cy12D72os1svmquTUNW6mpYF7Sd+cOVM9QPQrSW+ujtQ6pfYqerjZJzYherukvuoSnFI2R Mp5eqe6hVuKw7U6905FaNA1iUV7tzMQ1DURkkip17zatkd0q2jui6F10zwW7U/iQyu9jIxOi LzL5VAn0GGqjmo5qoqL3KhkAAAAAAAAAAAAAABVREVVXCJ1VTDnNaiq5yIid6qvcQTvDuZcL rdvSFoFq1F0mXkmnT2Mfn8ZPcA7/AFhvzorTmqY7HUVscj+ZElka7pH51UpBxS6ltupt0qqs tNUyqpO2yyRi9HIWSvVi2i0Pp2Sw61qm1t7uDF7WqVqPkjc7vRF9xSnO4lgorDqWSC1VPhVt fJmmkVfGVufKB6G8Jyqm0dIqJnxk+gl4iLhM+9JSe/8AsJdAAAAAABwr7cG2u0VNwexXtgYr 1anlOafhcaWOtoZqWZEcyVqtVFApJv8A722DUWo6PsaZWOoJWo9Fd5lLN7JbnW3cG1Ndbqd0 bYIWoqquc4TB53786dksm6l2pEYrWTVTljTHkVS8nBfpdtj2mpKmWPkqZ1Xm6eQCcwAAAAAA AAAAAAAAAAAAAAAAAAAAHkAXuArfqdUdxXR56KlG36Sx7fYp7xXHU3TisjTl6+Bs8nuljm+x T3gMgAAAAAAAAAAAAAAAAAAAAAAAAAAaVvRS+E7dXSN7ef7U5UT9Sm6nVasp46zTtwppEzzU z/oUDycsdMlVqxlve9zGT1To5ERcdOYu5unt3pC28N8MzKaOnmZAxUm7lVffKa1yw2Pc18k6 csUNWrnYTuTmUs/Seju/FNRWqilqKLTFvpFZO5uU53onTp5QKm81bS08dbHJIiJMrYXtXC5R fOWa4cOJqptkkGmtZSLLA3DIp3dEYnukI6lt0Wn73LYatFX0MkWRjHJ/GdfKc/cJ+ibxp231 lipquG8NiTt4WU6ozm98C2fFFd7febboe42urhqad92YrXMXJv24m2Fi3H0VDTXCnY2rbCnZ TImFRcHnbY9aXy3Vlnhuc9XJQW+qSZsUyLypg9FNmt1NK64sdL6HV7GVUbESSFyo3C+4BWO1 3Dcnh51F4JXJUXHTaydHIiqiJnuypava/dXSuvLXFU2yvhbUOROanV/jMXzKbNqjT9o1Ha5K G70cNTA9qp47c491CknEFtbddprs3UeirnU09NUO7R0ca8qN69wGz/ZCbX2aUV5a3DuZrEeQ /wANt6l09uHbbu9ytp1f90v8hjdndnU2t9CUen79ZpWTU7myJPyKquRE71U+uHS2R6qorxp3 PLXzcq03nynVQPSK31LKyhhqolRWSsR7VTyop+z/AOLd7xEHDRrVb3pyexXB/JcbVKtN2bu9 Ws6ZJfaqOblO4Dyw4hfCIt1bsqsfE5Z3491MqaZpt9el9pXUc0jKhZE5HI5cnoLxFcPVt3Bn S72xfBLg1vKrWJhH+6pAcPCVrqnqWywSNY5i5a5JEygG078bk6dqNtNO6QqeWrvD2Q89Uxes S+XK95YPZS8WSzbe263VOo6WrmYzKv5/P5Dz51xoS/WfXkGm7pMstbK9Gsersr34Jqt3Ddut FSsWnu80bHMRzUbN5wLoemmwc2fRemx5uYyuqtPJ33al+WUd1nstutpmwSXasvtT2bHIi4mz 3jRWym6up9PRXemvtT2ciqjczY7gLxemnT/5Wpvlj006f/K1N8spuvDru9y59HanPw4Xh13f 5sJfanHw4FxvTVp9qOc6702P0u4+I9YabmYr4r1SK1vslR5Tt3Dpu8rXIt8qF/8AfPmDhu3Z jjcxt6qGI7vRJu8C48GsNNTo5YbzSPRvfh/cfomqtPL3Xal+WU0h4b92oUekN6nZnzTd59N4 dN30b/PlQi59vAuSmqtPKqp6LUvT88emnT/5WpvllCNfbX7m6Ruduoqu+1XPXqqM+3ZNrpOH rd2opop232p5ZGI5Pt/nAuZ6adP/AJWpvlnw7VenmNXnvNKmV6LzFGdwtnt09HaWqr9XX2q7 CnbzPxNk6bZ/bncjcuwS3W2XyqdBHJyLmXHUCRNR6vsOieJarvt1q4rrSVsqdmqOy2D3SKuL C+zX7XUVzbVOno5Ysw8jvFa1V6Idtudw8a2sGnqnUV6qO3ZA3mkc+TKml3XazXT7ZQ1Mro6i mnha+H7ai4avcBHDZlSRqq5zmNVFRqrktjoLiE0HZNH0NprNKLPURRNa+TCdVQgdu0eskXPg kK4/vDPqUaz/AKpD1/vAJH4hN4dJa405TUFlsC0MsblVX4TqV8bK/HK6R6tTycym+O2m1kju tJB08naHz6k+sUXmWjh+WBN3Cjrij0foS71up6hs9sWByQU0i5V7vMmTb+EnUNgn1PqTUz7z Da6Kpq+eGilf1RFKlarseo9OUsdBdZFZBnLY2vyiKdrpHRGurhb/AA2xQzpA7rliqmQPTlut 9KInjX6jXPd45n08aTzj0do/lnnF6Qd21ROlb7njr+4ekHdtXYxW5T89f3Aejnp30qjsrfqP Hm5zKa40muf4do+n555xLoLdvGVSt+Uv7jLNA7trlWpW+746/uA9HE1zpNVwl9o/lnz6fNIc /J6PUXN5uc85E0Du0njI2t+Uv7jHqfbsK9H8lZzefmX9wHo67XekWu5XX6iRf0zKa40mq49H aP5Z5wO0Buw52VZWqv6S/uPv0gbtovdW5X89f3Aejnp40nnHo7R5/TMJrfSqOXN+o8L3Jznn Gmgt21d3VuU/OX9wXQW7eEVUrflL+4D0dTXGk1zi+0fT88N1zpNe6+0fyzzjZoHdtUVUSt93 x1/cYTQO7TUyja1M/nL+4C0nGNeLJeNCMq7bqSmetLOxz6aN/jPRFyaNrPdW0av2BZQ6bkZa 6mCJW1NPnD3IiYz085BtTtnuhVMWOopqmVruqo5yqinFp9qtw4nSRwW2aPnTD0blEVAI8WWT vSSRHfhLzL1JW4bNwrDoDUNZXX61+iEU0SMRvTov6zqm7N6+knbElodzr3dFOxbsLuQr+lmZ nHnAnS88S23dTaaumh0jyvkaqMXDenQqHeK1Kq7VVXT80LJZHORqLjCKvcSMuwu4+HfwO3v8 5+c+xm4sMSyvs6cuMdFA63Yivq6Hcq21VNWOpuzcqve53i490nzeXcLTOudw9P2i2TxUs9FP FJUXBq4a7C9W9CDqbabcSnej6e2yxOx3tyin5w7TbgNkWWO1ytk5sq7rnIHpLZtZaUp7dDT+ mGjldGxEV3P39Dl+nnSeM+jtH8s84Y9v92GNXkZWtT3HKPSFu1zcnLW57/ZL+4D0eTXGk1VU S+0fT88JrjSa919o/lnnD6Q92kciYrcu/OULoTdlnkruq/jKB6PLrjSad99o/lny/XmkWM53 X6iRvn5zzkXQG7S5y2tXH56/uPmTb/dhWcr2Vit83MoHo4mvdHrCsvo/Rcifhc5mPXmkXs52 X6iVvn5zzhi2+3XfCsbY6zs/xeZcfQZZt9uwxnK1lYjU8iOUD0fTXGk1XHo7R/LCa40mucX2 j6fnnnGmgd2+9Erev56/uMekLdpFXpW/KUD0d9POk849HaPP6Y9PGk849HaP5Z5xekDdpcO5 a35S/uHpB3bV2MVuU/OX9wHoRqbV2layxV9LFqSjiknhVjXc/sV85V/Yrc7S+hdd6ksN3e2o mq5XdlcVcitTovcqkKv293Xc3xmViov5ynXu2k3BllV77XI6RVzzLnIHW7wV9ZW68uFTV1j6 lJJHOicjlxyqq4wamySWTl55HORrk71z5TfqnabcGoVHT2yWRyJjmXOcG47XcOGtNR3mBtyp PBKBrkWSRF64AuHwneLtJR83Txv2EunR6H03R6Y03S2ekanJCxqKuO9UTvO8AAEV7wQ7lyVk C6Np4pIUX7YrpOVcASoYRVVypjonlK2+Db/838hhx8OZ8E4ge/wGn5f8R1AskYVVRUwmStja biCc5USggx8OZWk4gsKraGnx/iOoEbcZ2iJZd2bFNQwK9KlWukVE/OLg6EtUVm0pQUMLeVrI Wqqe6qIVn1NojenUNwpq6utlOs0GEYqy5NgSk3+ZG1iUECcrURESfzAWTBDG1cG7cep4natp Yo7fheZWy8xM4AAAAAAAAAAAAAAAAAAAAAAAAA07eHUVfpXQtde7fEsktO3KNRMm4nTa1tTL 1pitt0iIrZY16L7ygeet33+vNTuYurpIFSojiSFG8vmLybE6ruestC0l+uUaxrUMRzUVMHm3 cLDMzdR9iWNfHuKsRMeTmPT3a2zJYdCWy1o3l7GJEwBswAAAAAAAAAAAAAAAAAAAAAAAAAAH Eu+FtdW3yrA/6FOWcO84S01jkTqkD/oUDyo3niSHcS6RtVETnX6S8vBTqG2XnbLwSmjjjmpU SKREREV3TvKz6z0FJqSHUeoaaPnlomuklRO9ERVOJwebkekzXsVBXydnbapVSRVXud3IBt+7 OnLbdeLiG2VcS+CSSRo9renMiluKTabQ9PTxxQ2eJGNREblEz9BVzXMsNTxkUM0EiSxSOhe1 UXKLku6ncnkAqbxibbabhtunqe1UTKWqrq9IVkROmFIO1ZtRuLtVcIL5Znz1UPs0kp0Xlanu lpOMD2WjEwv87NJot9DS3DTcFLXU7J4XRIjmPTKL0AqpstxXNkdFZdbwuSdMMWfo1qeTqSbx CT2PWe0FTeLHWQ1y03IrUjdnHU6fePhf0zqpJa+xIltqeqpHE3COUrLq3SO7G1tPUW6Twt1p evsGKrkciedALhaN01pvWe17KqottOtUlF2CvRiJhUaVE20mj294lUoVdy08NSrV82FJA4Zu Ii3aSsq6c1fG+GN0yu7VzV5uvkwaBxFVtiu25kOptFSOqUqZUe5GN6oBY3dTS160bqam3Q0H C+WKZrVrKWNMq5i9XOwSRoPefReo7Wyae6U9uqkT7ZTzvw5qnL2O1HTau23o3Oa1/ZQpTzMX zomFRSKOKHaXS1r2/vOqrPA23VsLEeiQtxzLkCcGa70hyqq6joFTz9ofEeutF+zbqShXH96Q TtdsXaL9oG23WovdUklRAx7+ncqoapxC7PW/SdioX229VLXzPVq9MZAjfeq92qt4haKtpbhD NTNnTmla7KJ4xeCg3A0TFbqVsmpreitib/vfcK9af4S7JdrDbbo++1PbVMLZJHcvVFUhDe3Q E2hdwmactt1qbisio2Nr/KvmAtxxCa40ncNtKuno9R0M0rpGqjWSdcGeH7W+kaLbKhp6rUdD DKyRyua6TClbdoNp7Xri5vsd/vFVbrp1VlMjejmp3qS3Fwg2uNqsi1RWxtTuaiATx6oeiMLy 6otyKv8AemG7h6IRFT00W9UX+9IJ9aLQf2rrviHrRaD+1dd8QE7LuHohURPTRb0ank7Uyu4m ic5TVNuRE8naEEetFoP7V13xGt7jcOmn9FaXqL3cNW1uImqrGqnRyp5ALNJuHoXm501Pb8/C mW7iaKRVzqm3L5vtiFAdDaWjvF+oaW911RbrdccrS1DUXLm+csHHwj22eNk0Wrq9WPajk6d6 KB+/EvqvTFz1RpeSjv1HMkLl53MflG9SaLNr/RbLNRMfqe3tVsDUVFk65wQjLwfWmXCy6mrH qnsVVvcfacIlAiYTVteqJ3dANl4o9ZaUumz13paLUdDPO6LxY2SdXGhcBuq9O2bb+sgu16pa KValcRyvwqp5ztn8IFrkTE2p6yRvlaqdFMM4PrPEv3PqSrhTzNaB0XHBudBJp6ksunrxT1dL V5bOkTs9CrVu3B1XT0cVJBWK6KJqNYjkzhELgzcH1omRPCNR1c3L3I5pEO++zun9t62lttpr 5bhdKlEc2BzfIoEUxbi61kkSCKo53L3Ije857tY7kOaiLDLhP7s1nUFNdbBqNKeopnU9ZHh3 ZNTr1OcmqtSImPBar5t37gO2TWO4/V3ZS/NhdYbjuT+Jlx8GdSuqtRr0SkqUTzdm79xldVak wiJR1KY/u3fuA4Oq6zUt1+6b3BLhO5ytwiFt+ArWDrjaqnT9ZBE9InI2NVYnchUe83y819I2 Crgnjjz3uYqIWN+x8wIuoK2TK5Y/CfEBd1KOn5VRaaDPk+1oZbR0uOtNBn4ND9Ync7VVUx1P oD8FpKXC4poM/BoG0lMidaaDPuRofuAOP4HTc38mg5fg0PrwSk/q0PzaH7ADj+B03N/JoMfB oZdSU2FxTQZ+DQ/cAfglJS4600Gfg0DqOl5VxTQZ+DQ/cAfg2kpcdaaDPwaGEo6bmXNNBjyf a0OQAPx8EpP6tD82hjwOk/qsHzaH7gD8fBKVFylNDn4NA2nj5VzFFzfoIfsAPybTw8vWGLPl 8VA6ngVqp2ES++xD9QB+DaSmx41NBn4NB4HSf1WD5tD9wB+PglJ/VYPm0HgdJ/VYPm0P2AH4 +B0n9Vg+bQx4HSf1WD5tD9wB+DqSmwuKaDPwaBKOlx1poM/BofuAPxSjpE7qWD5tD58Dpub+ TQcvwaHIAH4+CUn9Wh+bQ+fA6bm/k0GPg0OQAPwWkpcdKaDPk+1oG0lLjrTQZ+DQ/cAfgtJS 4XFNBn4NA2jpcdaaDPwaH7gD8Fo6XC4poM/BofcMTIm4ZGxnn5W4P0AAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAHzJIyNMvcjU90/F88LkVqTMwqKi9TTN4tKX3VNngpbFfKi1TM l5nPi71TzEXps5uLzf0/uWANB1Lt4yXishcxjfBmMbUcyJ0znJcKOaFjUasrERERETJWybYX W0lz9FF1vX+GcvL2uOuDneo5uNypncC5OXygWH8Jg9tZ8Y8Jg9tZ8ZXhuzm4q9+vrkYTZvcZ FVfVAuS58gFiPCYPbWfGPCYPbWfGV3TZzcbmyu4FzRMdxn1HNxlaqen+5IvkAsP4RB7az4x4 TB7az4yu/qN7jKzHqgXNFMrs5uNnpr+5KBYfwmn9uZ8Y8Jg9tZ8ZXlNm9xO70/3Ix6je4qPX /wAQLkrQLDeFU/tzPjM+Ewe2s+Mrwmze4mcen65YC7Obi4/p/csgWH8Jg9tZ8Y8Jg9tZ8ZXd Nm9xleiruBc0Qz6ju439vrkBYfwmD21nxjwmn9uZ8ZXj1HNxfJr+5e6Z9RvcT+39yAsN4TB7 az4x4TB7az4yu7tnNx1RUTX9zQN2b3GamPVAubgLEeEwe2s+MeEwe2s+Mrw3ZvcbxlXcC5+4 hh2ze4yt6bgXNFyBYjwmD21nxjwmD21nxleF2b3FVUX1QLmnnC7O7jf2+uWALD+Ewe2s+M49 45VtFY9Fz9zv+hSAPUb3FVWr6oFz6L1Qm6ho6qg0StFWzuqJ4aNzXyu73qjV6gQHw226mvF9 1Zb6xiPpqmNWPavmyV14kNoLxt/qya426llktc0iyxyRN6R9eiKpZbhUXOsdSI1PFwv1ie7/ AGK1X+1vt93ooqqnemFY9MoB5ZaR3BuFq1tR6krnOqJ6ZzVRV6rhCxXryZ/Lb5PkoSFq/hH0 lea6Spoa51ua5cpHHH0Q6BvBjZkTC3+Zf8gERbs8R02tvQbNI6P0Nq0qEy3vwbtScYk0NJFD 6HyKrG4VeVDod7OHC3aGbYlgu0k6XGtSndluOVF8pv8AQ8HNlqKGnnbf5lWRiK7xO4DovXkz /k+T5KH4VXF5BWMWOtsjahiphUkiR30m1+sysv5fm+QPWZWX8vzfIArDvBrLTmsqzw212x1D UZy7oiN/0Ok271hJpPUENyZE2djO9kicyf6lufWZWX8vzfIHrMrL+X5vkARVs1xCU2htRVbp IJpLVVudK+Jvej183uG67w8UOm9Y7eXHT1HbqiKeqYjWuf3J1Ng9ZlZfy/N8gesysv5fm+QB 1O2vFVpjTei6KzVNsqZJ6eJrFc3uXCGub7cRmnNcWy3U9voKmGSnfzSK9ei+8bz6zKy/l+b5 A9ZlZfy/N8gD507xdaStmnbbbktdWr6aBsci56KqEDb1bvwan3Pp9ZaegWCSlekkTZkymU86 E9+sysv5fm+QPWZWX8vzfIAiTarfK3W/XKa21dSrNco2OjjSmTlbyr50JoXjI0nn+aqv4zhe sysv5fm+QPWZWX8vzfIA5vryNKfkqrHryNKfkqrOF6zKy/l+b5A9ZlZfy/N8gDm+vI0p+Sqs 0nefiQ0dr7Rk1kW21kc2FWNyu6Z902n1mVl/L83yB6zKy/l+b5AFc9M7q1E1RZKLUccUlrsy ckDYW8r1bnzllaXjC0fTUkNPFaqzlijRnVfMcb1mVl/L83yB6zKy/l+b5AHN9eRpT8lVY9eR pT8lVZwvWZWX8vzfIHrMrL+X5vkAc315GlPyVVmXcZGkvwbVV/GcH1mVl/L83yB6zKy/l+b5 AHN9eRpT8lVfxkI7671WfVOrKLVmnKWWG40rUaiT+M3CL5iYPWZWX8vzfIMpwZWX8vzfIArN btwUvm8dr1lqyCKaNszVqY42IiK1OncXhtOrtk7nb4qxZrPTdo1F7N6N5m++VX4lNgabbC2U lxo7i+sjmcqKjkxjB1XDztxo7W1qqqjUepH2yaOXlZGnlQC1Gt9wtldM2vw6OK23F3XEcCNV xHTeJTaJ3T0muT/2mlc9+NJWLSWq322wXV1xp0xh6k1bN8LdBq/RMF8rLxLBLO1HNjRuUwoH S727z7eau0e212HTq0VVlftisRDvvsey4vVc3v8AH7/1G3rwY2ZW49H5kX9AmDYzZizbX00z aOoWqmlXKyObhUAlMAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAw1uFVcr1MgAYa1EVVyvUyAAAAw5qOTCqpkAB5DD G8qYRVMgAYVMoqecyAPlWJycuVPoAAYY3lTGVX3zIAw1uFVcr1MgAAABhWoqouV6GQAMOTKK hhWorUbleh9AAcO9L/BNa3H/AA7+v6lOYcK9KvoTWpjp4O/r+pQK/cKfL6ctSMTzL9Ysc1MJ grhwpN5dX6kz0XC9f8xY5nsE6590DIAAgDjA9lozqv8AOzScNPfzLS/BoQhxf9+jP/67ScNP /wAzUvwaAc4AAAAAAAAAAAAAAAAAAAAAAAAAAAABhGojldlepkACE+Lbby7a+0bDBaXN7WmV zuVfLkp7S7BblwoqQRzQon4iObn4j0uMYTzIB5qR8PO49dWtinikc56oivkaq/SX22U0tUaS 0BbrTVvR88ULUfjzobojcOVemPNg+gAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAB8udjuwq+bIH0cO9c3oTW93L4O/6FOYhw7yqehNY3y+Dv+hQK+cKi41nqRO9qIv1i xzVy1FRMFcuFNFTWupE/B8nyixwAAAQBxgd+jP8A+s0m/T/N6D0mMY7NMkI8X/stGf8A9dpN 1gVfQikREyixp1A7AAxzNzjKZ98DIAAHCvV0orPbpa+4VEcFPEmXPe7CIc0q9xaanqtR6jte 2Nind21fL2dUjF7k7+oFkbDeKG90SVlvmbNCvc5q5RTsDWds9Nw6V0dbrPFHyuiga2Vc97kT qbDVzdhTSTYzyNVcAca9Xa3WejdV3OripYW975HYQ/DTmoLXqCk8KtVVHUw59kx2UKj7t0m4 m5817qK2Wos+nbasjEZ5JVbnCkgcCyOZtqsavVeR7m5Vc9ygWNBhnsE6590yAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAjzWm7umtK3j0MuLK lZuXmyxuUJDNWv8AoLS19r/C7pamTzYxzqoGl+uC0X7XW/IK37n8S2orTrxZdN9aHC5ZNnzl tU2n0InVLJF8alYd4OHC96i3D7SxUT6G2q1UWREyneBz9H8Y8WYmaipFRPw1iYTHpzf3Q2r7 dVQ2+eRkrqd/STCeQijRvB1QUyRy3u7MnVe+NWYJfs2w+3mmrPUy0tmZ4Q2By9ojl78KBDWx O5Ng0pq6/wDoi2ockiLhWJnykwN4hdE8nSKtwn5hGvDno7Tt41bqFtyt7Z2xovKir7pOTNqN BuajkscXX3QNaXiD0UiZWOs+QE4gtFqmezrfkGyrtLoNe+xxfGp9LtPoVcfwJF091QK+8RG6 emdV1WlIaBtS19Pc2ySc7cJyki37iN0LpO1RQ1KVTpGMRERqZypqfFBojS1jk0jJbrWyF8t1 ayRUX2TfMSRX7H7daltMMtZY2LK6NF5lcveBAGr+MasekjNP0bETryrKzCnD2I4hL1eNwGz6 rqmx0iuyrWOwhuWsODy0VjpX2W6Mo/xY+XODptmuGOqsWuUXUtO6utrXeyxyoqAWCpN6NGVN Uyniq1V738jeqdVJDpZ2VNOyaNcscmUNCptmNvKaqjqYbCxskbkc1edeim/U0MdPA2GJvKxq YRAOn1veafT2mbhd55UZ2EDnNyveqJ0Kc7Ha50rUbj3jX2r53PqJJOakRFRezVFx+okzja1D WutFu0jbpXQzVtSxr3p+K7obFtfw7aDt2jqaG72llZWyszNKrlTmyBKmjdXWHVFH4TZ7hDUZ 6qxr0VyfqO/c1HNVrkRUXyKUz1Vb5Nit77d6Xpnss9wVrXQ5XDVcuPKXJpJO2pYpUXPOxHfG gGjb108VPtpdm00TI0dE5XI1MZXCkY8DH3vJM+2v+sShvllu2t1y/wD3Tuv6lIv4GURdvJEX 21/1gLFpjHTuARERMIAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAACoi96HHr4X1FHPTpjEkTmIvuqmDkACKtmNtqzRd/utfUyo9lZ7FEd ny5JVRMJhAAAAAjXfLb2p10lhWmlRi22uSodl2MohIVsgWloIYHd7GohyAAwmc46gAAYcnM3 GcGQBWTjUsddTttOr6WCSeOjqo1kaxuVRrVyqkoba7s6Q1JpGluTrtS0j2RpzxSyo1yYTzG/ 3i2UV2t8tDXwNmglarXNcnkUhC+cMGg624rPRxPpmK7L2NkciKBF26l0i3h33tNs0y189Hb3 MfLNjxcsd16lxqNjo6eKNUREZG1vxIaftnthpXQNMrLHQtild7KRVyqqbsBo2+DUbttdcrlO xd3+8pFnAxh23kqIv+9f3fpE86ns1LfrPPbKxvNDM1WuQ6TbTQVn0JbHUFoiSOJyquPfXIG2 tTCY7zIAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAIiIqqidVAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAMI9qu5UcmfMZAA/KpqaembzTzMjb53Lg40V4tcr 0ZHXQOcvRERwHOATqmUAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAeQBe5QK5M1Xfl4nILIlxmSgWB6rDnxVXJN+ u9RwaV0jXX2oRHNpYlfyr5St01ZRUPFnBPca6CkiSnf48jsJ3kqb73nTt/2uvFuodRW9ah9O qMTtUXIEG2O37q713aqvVPe6yz2VJVSJIn9FavcbHXcO+vKOlWotu4N0kqmplrVXHU3PhB1J aK/Q7rHFVQpWUTkiexrsK/HlRCbrhW0tBAs9ZUxU8LernyLhMAVu4fdw9WWjXbtuNdPfLWvV ewnkdlXNb5SzRUe5XWh1rxY2eTTapLDRRPZPUR9Wqvvltomq2NrVXKoiIB9AAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAACFNzuH+0601Kl9kuclJUI1Uy1pq68LtuVMO1XUr5/F7yVd4d0bDtxafCrm5ZJ39I4GL 47s92EISTievEc/hc+kLq22ouXSLTrjl8+QJL2e2MtW3l8ddaK4PqJHIuUVuM5Nr3e0XUa30 76DwXKSga/KPezvwppl/4hNJUO37dQ00vb1MiIjaNjkWVHL3dCLGb+bsSM9E2aUqfQ7PMjVp V5uUCbtmNn9P7dUzlpOWqrl9nUub4yqSaRhsdu7aNxaGSJjHUlyp15ZoJejuby9CTwAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAGGrzJnCp74GQYa7mz0VMecOdjHRVyBkAwi+MqYXp5Q MgAADDlwmcKvvGU7gAMK7DkTC9TIAGEdlyphUwZXuAAw1eZM4VPfMgAAAAAAAAAYc7GOirnz GQAMc3jcuF98yABhjuZF6Knvhy4aq4VfeAyAnVMmFdhUTCrkDIAAAHX117tFDO2CsuVLTyu6 IySRGqv6gOwB1tPqCyVErooLrRyPamXNbKiqh8JqXT6xukS80KsZ7J3bJhAO1B0/pmsHZtmS 9UHZL+F2yYU/STUdhjkbE+70TXu9i1ZkyoHaA6lmptPvqVpm3mhWZO9iTN5viMs1HYXte5t4 olaz2SpMnT3wO1B1Ppm0/wBj23ozQ9mv4fbNwfcuobHErElu1GxX+x5pUTPvAdmDq26jsK1H g6XeiWb8Ttkz8R8+mXT+HL6M0OGey+3N6AdsDiW252+5RLLb62CqYn4UT0cn+hywAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAB8P5uZvL3eU+wBUX VFHT674qKO1ajd2lHTQuWOJ/cqtXoWim0zY57Otrmt8D6NWcixq1MKhBvEftlfnajptwdF4b c6NiNdGn4Sd69ENKfvpu5V2/0Hj0vNHcXp2farSqjUXuzkDVdEaEsE/FnJYnsZJbWrJI2DPi tVq9ELwtpKSOkbSJDH2PLyIzlTGCl8uz+42mmeqjSzJLfnuSWSFFVVRF6qmDaIuJ3UUVlWlm 0nclvDG8qfcq8qu7gPyrrbS6L4tLWywYbFcI5JKiJncrvdLaRqro2uXvVEUq/wAO+hNT6i16 /c7WUaxTq5Vp4XIqcrXeTCloQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABqW6Fw1Db9PyTac on1dYiLyxtXqqm2jAFbE1nvcjG/7I1arjr4yHV33dbdmxz0kFy0xURPrX8kKK9PGUtOU74yt cuotx7BQRVCtW31SSORHeRQNxbrTe5zGvTSFUrXJlF5k6mfTpvf/AGQq/lITnt9cvRbRtqr2 uR6TU7XKufcO/Arb6c97v7IVfyh6dN7/AOyFX8pCyQArb6c97/7IVfyjDdZ73onXSNWv+ZCy YArb6dN7/wCyFX8pB6c97v7IVfyiyQArb6dN7/7IVfykHpz3u/shV/KLJACtvp03v/shV/KQ enPe7+yFX8oskAK2+nTe/wDshV/KQw7We96p00jVp/mLJgCti6z3vxhNIVef0kCaz3vxj0oV ef0iyYArY3We96J10jVr/mDdZ73pnOkatf8AMhZMAVsXWe9+P6IVfygms970TrpCrX/MWTAF bfTpvf8A2Qq/lIPTnvd/ZCr+UWSAFbfTpvf/AGQq/lIPTnvd/ZCr+UWSAFbfTpvf/ZCr+Ug9 Om9/9kKv5SFkgBW306b3f2Qq/lD06b3/ANkKv5SFkgBW5msd7nSwoukqtEWREd4ydE8pP2nJ 6+azU8lxgdFUuT7YxfwTswB8yuVsT3J3oiqebnFjqu+LvVXtZcpUZTK1YmtdhGqejV3d2Vsq 50XqyB6/EinlZvXc3Xbcy6VkqoqvfyqvvKoHXWfXuqbXWy1dLdZmyytVr15l657zit1hqNtL NStuc6QzZ528y9cnScqK9WtVMJ5QiNRqq5U9xEA7pNV6g9D20fopN2DFRWs5l8h+lTrTU1TV xVU11ndLDjkdzL0x3HSKyPsuZHJzebJ8I1OdEVUx74HdQ6u1DDdXXSO5zpVuzl/MvlPuDWep YYZ4o7rOjJ0VJE5l657zo0a3tVark5fOfKNyqoip0A7tNXahS3pQeic/g6dzOZTkXDXWqK58 D6i6zuWBE7Pxl6Y7joXMi7FHNd4/lTJ+bUakiI5U5fLgDvo9aalZdPRNt1nSq/H5lPzXV2ol bM30TnxMqq/xl657zrYmUa1iNe53Y+VU7zjy8iSORi+Ki9M+YC3v2PvVNzkudztFVVSTQeKk bXLnlLrlAOAad0eu6mNEyj3NyX+a7mz7i4AyAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAACoiphURT8vB6fn5+wj5vPyJk/UAYVrVbyq1FTzYOtf YLQ+r8KdQQLNnPNyIa/qXcWy2LWVFpaqSVa6sZzx8qeLg3JjuZjXJ5URQDGNY3lY1GonkRMG QAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA/GtmSno5p17o2K74kyeXvEzqF2o93rrcUl5 m5RrevmPTq+0Trhaaiia9WdtGrFci9UyhRXebYCjsGs7TB4bLJ6MVSscrndUyoFieDXUyag2 uii7TmdRcsK9e7oTeRDw77Sx7Z2uWGmrJpo6ledyOd0yS8AAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAddqZyM05cnOXCJSyZ+Sp5dWS10mp97Ke1VCo6nq65Y3+9lT0713UMptH3WR/ d4LIn/xU81th6ZKvf22KiKqJcXL/AKqByeI3RFn0XrWjtNqajYpETnVPfwT/ALP8NektSaOt 17quRzpFy9uF8ZCIOKuoSq3ihglan2uXkTHmyXg2KpW0+2lsiYitRG5x+oCM4eFHQzLhJO+F joXIvLH16H5UfChoiOmqIpWRyTPReR3XxSxgwmc46gVzqOE/Q7rSyBscbKluMzdepmfhQ0U6 eCSJjGNZjtEwvjp5SxaoiphUyAK7v4UtCeiKzJDGkS90fU/Gl4TNEsjnSZjJHPzyLhfFLHYT OcdQqZRUyB5/8Uuytk25slDNbEa+WVq8zk9xTodAbaWG97DVmp3xtfc4ZXJnyo1ELAcfEDn6 MpHNbnlYvjebqRxwvRTXPYzUduja1eziml6+8BqnA3VOp90G07e6SREU9Do+bLubz9Dzf4Nn ui3qomK9Gp26ouV7z0iAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAYe9rG8z3I1E8qqBXPeNWpxHaccvT7lX6SxVN/J4/0E+grnvE+JeIzTju 2iVi0qrnmTp1LEUUjXws5Hsc3kT2K5A/cAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAK7 cTrc7gaK71+7/iLEld+Jvm9UHRSJ3eHdQJ+tKYttOn5iHKONaf5tp/0EOSAAAAA/Oongp41k nmjiYne57kan+oH6A6z0w2HCr6M2/p/zDf3mU1BYldypeKBV/wAQ394HZA6v0xWHn5fRm35/ xDf3n03UFiVFVLxb8J/zDf3gdkDrE1DYlx/DNv6933Q394XUFiR3L6MW/P8AiG/vA7MHWJqG wrj+Gbf17vuhv7x6YrDjPozb+/H8ob+8DswdamoLEqqiXi35T/mG/vPlNRWFXK1Lzb8p/wAw 394HaA6xNQ2JW83ozb8f4hv7zCaisKt5kvNvx/iG/vA7QHWemGxZVPRm39P+Yb+8JqGxdP4Z t/X/AJhv7wOzB1npisOM+jNv78fyhv7zKagsSqqJeLf07/uhv7wOyB1bdRWFVVEvNv6f8w39 5ldQWJGc3oxb8f4hv7wOzB1aaisKpn0Zt+P8Q395n0w2Lr/DNv6d/wB0N/eB2YOs9MNizj0Z t/dn+UN/ePTDYuVFS8UCovmnb+8Dswda2/2NyKqXegwn/MN/edHftx9I2Zrlq7vTLy9/JIjv 2gflvRVeB7eXOXlV2YXJhPeU88NgdR2rTm60d3u2Gwx1Ku5lX2PVS12+m/GharQtdbbdXPmq 5kVGpjp3FEbPX+C3d1V4PFUNV6u5JO5eoG/7ragi1ZvKtyt7kmgfWorFTzcx6Q7bw9hoy3R8 vL9pb0/UeTz62VbxJXQNbTrz86NYuEavuG80m9mv6anjghvNS1jejU7VQPUoHl0u+24XP/PV V0/vVPpd8txF/wDzdSn/ALygeoYPLtN89w3O6Xup6f3qmE303DcrsXuq7vbVA9RTDvYr5Ty7 TfXcJrU/hqq6/wB6pn1c9w+Zf4aqu721QLecckLl2vkmaiIjGftK68Nu4dl0noy/W65TNY+r pJWMyvlcnQjjUm52rdWULrdd7nPNTuTDkc9VQ1yxXaO2x1ETqKCpV7VaiyJ3e6gEgcLtRGze 22PV+OeoVU93qenMC5havnQ8oNltQUWm9zLXe7gqtpoJeZ+E7kPQK28Qm289FHMlzkb4qIqK ncBMAIoZv5ty7GLq/p50Cb/bcq/Poq7Ke4BK5hrkdnC5wRDcOIjbeipn1LrlI7p3I00K4cX2 i4pHNpGyvRHd6xgWcBXjTnFhoC4VSQVEs0WfL2eCadK6vsGpaJtVarjBK1yZRvOnN8QHfAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAaruy2v8AU/uz7ZIs dYyBVicnkU2o/Krp46qmkp5UyyRqtVAPKbU+uNYSasfUVtyc64Uj1iY5U6p1L88JFRqC5bX0 t21DVrPUzKqdU8iFJ95NHVFFvpUW6GLpVV/MxPzeY9Gds7LFYNF2+3RIiI2FrlT3VRANkAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACFd+tH3vUOsdLVtsic6Giq+0mVEzhCagBx7bG6 Kghjd3tYiKcgAAAAB0OudNUmqbHLa6xz2xPRUVWuVqnfBUymFAgRvDNpPlanhNaqJ/zDupH+ 9m0+j9CUNqmSsrEfWVjYHJ4S7oi+UtyuWs8VEKQ8fOrVTV1FZIpMpTck/Re5QJctPDjo+vt1 PWQ1dY9sjUdzJUu6nK9bRpNqqvhNaiL0/lDjbOGS/svu0lol7TnkZCiPXPUk1URe9MgQI7hm 0ojU+6q1Md6+EOPtOGbSXL/KK3OO/wAIcTyqIqYVOgTomEAgVnDPpLGFqa1VT/mXD1s2k+b+ UVuPN4Q4nlERFVUTqpkCBvWz6RRetRWpn/mXGG8M2k0zmorf+ocTyqIvencZAgVvDPpJVVUq a1W/4hxleGfSKJ1qK1P/APJcTyiIiYRMIFRFTCpkCBU4ZtKcqotTW58/hDgzhn0ljHhNaqp3 /dLiejCIiZwneBAycM2k+Zfuitx5vCHGfWz6RRceEVuV/wCZcTyYVEznHVAIFThm0kjV5qmt yvd90OMu4aNJ8iNWprebyfdDieVRF70yFRM5x1QCB/WzaS5f5RW/9Q4wzhm0ly9aitX3fCHE 8rhEXKpjy5IN393+sO3lLPQUEzKu7KioyJOrUX30A1LWe0O1ujoHT36+S064y2N9W5FX/UrX ujqjR1JK6j0m2vRzVVO28JVUX/U0vcTXV91veX115rZXo9+UiV2WtTPkOltltp6y909Ek3LF M5Gq9fIBhb1dn8zlutW3Pk7VxxlrLjUuRrqqqlVe7MjlyXc2w4TtMPtVJdbhc5ant2Nk5MIq dfITRYNldu7YiMTT1FUOYne+JAPLyalrmxqs0U/ny7J+VOxFyrsoiHpVvvtlp2Xbqu9A9NUL KxjVc1zI8KiIinm5X0VZTVc1PJTTse2RyK1WL06gfEaRPRWsY5z1XCInlOybY7i5qKloqVRf Lg2zYHTVTqDcm30jbc+eNFRXo9i8vRT0J1Xbdv8ASGl33S7WW3RRQQIvViZcqIB5g3C3z0XI lXQy0/MqdX+VCRZKDbmj0VSXSVnhFbI/lkhbJ4zfdOr3t1vTa11XNPb7fDRW+F6sgbEmOdvk yhJ3C3sFLrpX3jULJaa1on2pOXq5feUCL9bU+h26cgqLE3krJGorm8+VavmNYtem71cKZKmi tFRUQ93OxOhJ/ErszcdudRyVVLA+W1TuV0T0TKNT9h2HCzulb9KXyOyaiooJ6CocjWvkTPKq qBFXpP1F1/gCr9zxTCaO1L3rYazH6J6n2my6SulBFXUVtopYJWo5rkYinKXS2nUb/NFJhPzA PKCv0zfKKB1TU2aqghb3ucnRDr6WlZUNcrV5VTznphxBaTttRtHeWWuzU7qrssxo1nU80Kyk r6WrnidTVEcjXqjm9mvQDjx0s0tWlNTtWWVVw1G96nfN0lqprE/gavRFTKYz1Ns4bNP1113Z s+La+phbL9tSRi8p6U0+lbB4PG2Sz0iORqIqcncB5VppLVfks1w6++dbc7fdLZUtiuEFTTOd 3Ne5cqeqGtKbS+mdM117q7TRtipY1d1anUo/ozStdvpvFNULF4NZ4Jlc1zE6K1FzgDr9teHX VWt7LSXelrVho6lcI56KuDbd1eGWLQuh2XmouUVRN2zInI1FTvUvBpKxUWm7BTWe3xtjp4G4 aiJgivi8q6Fu2HJJUwpIlZF4nOme/wAwFc3cKN0uOkIb7ZrpEr3t5uyRF5l9wilU3H2j1Aj5 UraHs35R0meV6J5j0W2YqKefb+gbBURPXk6o1yKqGd1NurFr3Ts9uulNGsyt+1z8uXNUDQOG 3fe1bgWyO33GVtPdo2oio92OdfcJzPLrVtjvey+67Wsklj8GmSRrkXCPbnuJZ3V4pLpcLFa6 TTUqx1DoPuqRFwrX+4BewHmD6v8AuJ+War5xR64DcT8s1XzigenwPMH1f9xPyzVfOKPV/wBx PyzVfOKB6fA8wvV+3F5eb0ZqsfCKY9cBuJ+War5xQPT4HmD6v+4n5ZqvnFHq/wC4n5ZqvnFA 9PgeYKb/AO4i915qvnFMu3/3FRcLearPwigenoPMH1f9xPyzVfOKPV/3E/LNV84oHp8Cgmxn EnqSh1hTUmpql9TQ1DkarpHqqtVVwhfS31UVbRQ1UD2vjlYjkVFz3oB+4AAAAAARlxEbnUu2 2i5K9zmuqpsxwsz15lToBJoPMiv4h9wqmslnbdKiJrlyjGyLhD8PV/3E/LNV84oHp8DzCbv9 uK5cJear5xTHq/7iZx6M1WU/vFA9PgeYPq/7iflmq+cUer/uJ+War5xQPT4HmD6v+4n5Zqvn FHq/7iflmq+cUD0+B5g+r/uJ+War5xTLd/txXLhLzVfOKB6eg8wfV/3E/LNV84o9X/cT8s1X zigenwPMu2cQ+4dJWMqHXKedsa5Vj5Fwperh73KpdxtFw16OalbExEqWIvsXASUcG53i2WzH h9ZFT83dzrjJzjRN0tuKfXLYUmutVQdkmMw+UDvvTdpxHZ9GaXHm5jLtW6dVMJeKVF/SIk9b hQ4RF1bdVx7xn1uVF/a26gS03V2m8fzxSr/mMN1bpzmd/DNKvuc3cRKnDjQp3atuoThxoUXP ptuoEtrq7Tad93pflmHat070X0ZpURO/xiJV4caFe/Vt1HrcaHGPTbdQJb9N+m8Z9GKXH6Zh dXacV3S80vTvTmIl9bjQ4x6bLqE4caHOfTbdQNP3R07p688QdkubLpS+DNgV73Z6ZyWHptUa aihjYl3pfFYjfZ+YqRuHtUtn3hs+n4NSV8kdTAr3SuXxm9e4l6PhyonxMd6brtlWoqgTNbr/ AGe4z9jRXCCeT8VjsqdmRhtttBS6MvSXOK/V1a5EXxJu4k8AAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAcG/3Btrs9TXuTKQsV2AOn1rrvTGkIOe+XWmpXqmWxvfhVNf0rvRoG/1SUtNfqRk zlwxjpEy5Svu2WiZ97NwLzqLVNdLNbqKrfDFTO6txnoSNrnhl0xWUC1OmXLabjAnNC+BuMuA sBG9kkbZI3I5rkyip5TL3IxiucuERMqVR2+3d1JtffWaO3MglWkV3LBXOy5VTuQszRXaivVk dXW+dk9PJHlrmrnyAcPSmsbPqOur6O3TtkloZeymRHZw42IrZwmJjX2v/wD+qpZMAAAPxq39 nBJIrkRrWKq/EeXvEheJ9Q7n19Y6ORWscsTVX3FU9RpY2SRuje1HNcmFRSsPFhorTFubp2oo bRTxTVV1Y2ZzW+yRV65A6/7H7qSSosdyslTHIxaZWtj5u5S2BquhdH6csNBDPZ7VT0cj2Ir3 Rtwrlx5TagAAAAAAAAAAAAAAAAABoe+OvaPQOhq26yyNSoRi9kxV9kBHXFbvdS6GsktmtFQx 92nbyqjVyrUXylAKqpu2qL458vbVtfUv8VqKqqqr5jk6z1BcdX6mqLpWzSVFRUSr2aOXKoir 0QuDwcbFwUNBFrDUdI2SaZEfTMe32IHUbDcLNHXaaluOs43LUzxL2EWVarFVOiqVx3l0JW7f 64q7RMx7YWP+0S9yL7x6ssYxiIjWoiNTCInkQhHiw2optc6Lnr6Onat1o2K6LCdXr7oGg8Eu 77LrbfSje6pFq4v4hznfgp3IWuTHeh5F2C4XTR2rWVELpKasopkSVE6ZwvVD0y2F3Cotf6Hp LjHK3wtGIk0aL1THQCQJGMkYrHtRzVTCoqd5oN62d0JdrrJcqu0sWeT2StwifFgkA49xraa3 0UtZVytihibzOc5e5ANLtekdD7bW6ru9NSw0cbEV75JMd/mRSmG/m4ep949T1Vp0vT1M1qol ykcXxKq48hzeLLfaq1XdJtNafqHMt0LlZK5juj1QjPZ2g3CnlqpdF0szXvZiWRMojk98DW9J R2206uYzVNJJJBSSfbYUXDsopbqzcW2irNQw2+3acqYYImI1GtVE7ivFy2V3TuFwmrqqzc80 zuZ7ld3qcddi9y0XK2Juf0gJ813xO6F1lpyqs1107USRyphrlVMtX3ypiWqovOopafT1JNKr 3qsUbOrkRV6G8eoVuZ1/gJvX847HTO0m7mn7m24W21OinTucj+4DcNq99tYbU0y2HVduq3QR YbGx7fGRDf28ZdA7us1SqEQUuorhYtwKf1V7Gysp3u+2PnarkQ6XiJuGlbhrOnptE22mpKKS JjkWJMZcvkAnp/GPbpEVkliqHsVMK1URUNIue922lyuEldV6PqFmkReblREQhuHbTV1VCyaK Cm5Hplv25EP0Ta7WS5VKel6dP49AJz0hxIaI0r2noJpOeF7u97kRV/UbL68mi5cegtVkrM3a 3WSJz9hTKnw6H07a/WSeMtPS4+HQCTt6+Iq57i2dunrXST07J/Ekav4eSxPCRpu16F28Ylwu NKlbWKk3VcOaip3KUTvel9RaV7GtrWxRqq+I5kiOVC2eyG1jdf6JgvMWubpG9ERj2NTo12O4 CbN6t0bZozRFbc6Suhmq+zXwdrVz4x5za715qfW9xmrrpWyva+TmSNHKiJ+osxxIbEXKxaEk u1NqS4XVlK1XSRyp3IVJtUtNDE9tQ9zH57sASPstu7qjQepaJnh7nW50iJURvXPi+55j0W03 rSx3exUV1bcqeNlTEj+VXdUyeUUFFPd7zFS0LXSyTuRrMJ1yXp0Dw71M2jbXLUazulLNJTtc 6FqdGL5kA7Hiv0HpfW+kqq8wXKlZcKKNZEXm6vwncUFqLHcYYXTNgfLEzo57U6IXh3N2MZp7 Qt3u1Trq6SMgp3P7NydHY8h1HB3trarrp+ruF2WO6Uc65SOXComQKUQSMjXxmqq+U7Clio52 OVz2x58iqXe3Q4S7DdnS1un6h1JK5VVIWNRGlctc8Oe4OmpHzNtvhFK3uejsrj3gI1ZQ0uVx Uxud5MH6R2lHLzK9rsd2D8KuxXu2yrHUWuoa9F7+zU/OOa5woqLS1Ce/GoHMdamvbhU8pxpa Nkc7Yo41ld+b5Dv9M6a1hqKF01rtksjGrhVVqobhoTR+uNOX1LlVaRjubc5WKbOAIvmo3MmR s0D4ubplydDlraka1Gtx18pK28VLqvUdE2ZugqazRQ4crqdFVehEDrpMzMcjVY9OioqdUA5L LS1iKnMme8+PQpjno78L6D8EuzkXOOvnMturld0TqoHIjtbPGxjvDbUj3ZVU6dyHH9FnNVUx gJdXOXCJ1XygcSuY+hqmrG7DmuRyL5lQvxwUbos1RpJNO3GdHXCjblXOXvTyIUFuE6TvRy+y b0Nu2S1tU6J1/Q3WKVY6dZWpUIi9HNA9XAdVpG+UuotO0d4pHtWKpiR6YXuydqAAODqC5wWa y1d0qnI2GmjWRy+4gHIraiKkpJaiZ7WRxtVyuVeh5r8Vu5VRrnX89PTzKtvpndm1menM1cZN /wB7+Ki5XukuOnbHSRw0r3craljsOwVcklfNUOmequke7mcq+VVA7ajtizwK5XJlT91tXVI0 VM46nDhuLomIzGFTvPt11cq5wqKBy0tTWM6YXB8NtDWuyneqZPxZdZPGcmcHyl2eiL3gcp1r asSq7GD5jtLe9XIq46IcdLs7lwuVMpdlz3dQOS21o9FRUwGWxM8uMInlOOtzky7vMJdX45uu EA/dbS10itRU90+1tSNb0wpxFurs5TKH026ycrndcAfs20Na52E8hl1pSSPCORFOO27vRMdV CXZyZwneBmutqxUquVUVU8xK3CHuY/RGu4qKrmVtsrH/AG5FXpnuQiSW4PmhfH1XodZBI+GZ krFVHMcjkVPcA9jqGpirKOKqhcjo5WI9q+4p+xXrgx3Pbq7RzLLXzo640qdyr15E6IWFAAAA AAAAAAACuO8a8vEZp1cZ+5l+ksVTfyeP9BPoK67ycycR2nORM/cq5+MsTTK7sY0VOnIn0Afq AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABwb/b2XSz1NA9cNmYrTnACnG3GtqjZHXl4sGp6 CdLbX1bpIZkTDcKvTqWy0peqK/2OG6W93NTzJlq5ydfrPQul9XMa2/WmnrHN9i57eqHaabs1 DYbTFbLdC2Gmi9gxvcgHR7i7f6f1zZprfe6Nj+ZPEkaiI9q+RclZpfT9w/XSWFW1F30xKqph iK5Y2+6pcXmTm5fKahqa+aPr7pJpG8zRzVMyI1ad7c5yBBXBHd4b/fNZXmBjo4qu4do1ru9E UtKanoDQOndFrVtsFFHStqH872sTHU2wAAfhWPeynmc1McrcooH6q9OuPGVPIhFnEFoa56yp 7ElukaxaOvZPIip+CileLjqbeK8bsX6LSVZU1MFBUY8H58NVDdtM8St3sVWlp3B0++3vjXld MiOdkCztrhdT0EMLu9jERTkml6G3Q0drCJrrNdY3uVPYv8Vf9TcmPY9Mse1ye4uQPoAAAAAA AAAAAAAAAHxUTRwQPmlcjY2JzOVfIh548ZW5z9W60fZaSVy0NverF5V6PLR8Wu5lPonQc1JT zoldWIsSNReqIqd5532qkrdSaiipmyLLU1UvjK5e/qBL/CNtO/XOr4rnWxqlupHJIiqnRXNX uPRmhpoaOkjpqeNscUbUa1qJhEI72C0dZ9B6Do7dDUU3bysSWRedM5VOqEhpW0arhKuDp/eI B+5hzWuarXIioqYVFPy8Kpv6xD8tDPhVN/WIfloBR3jY2g9Bbkur7FSu8ElX7e1qZ8Ze9SN+ FvdKfQGt4oaiZzbZVvRkyOXo1D0S1haLVqfT9VaK10Esc0atTLkXCqnRTzK3z2+rtv8AWdVb pER9I6TMEqL39cgeoNuvFHcLRFdKWZrqWSPte0z0RpTXjC34dX1Euj9MVeIUy2omY7o5PMik Y6d381hR7droeljfzzOSOOp5sK1vdy+8RzrfSd5sD46i78vaVTuZFR6O7+oHd7LbcXjcbVkN uoo3+D86OnqHJlvReqZPSjbXQ9k0Vpunstto42pE1OZ6tRVcvl6lF9oeIyHbbT6Wy2aRo5Jl x2k/NhzlN4bxtXZM50nTr/7qgXWWni5k+0xY/RQ+vB4PaY/koUnTjau3KqelOnz5+1UynG1d sJ/snT/OqBdfweD2mP5KHyynix40MWfcahSleNq75ymlKZE+EDuNq7KvTSdMn/uqBY/fbaWz bjaYmpn08UVexi9hKjUTr7p506s0Xc9Nawdpy8I+nlSTljlk6JjOEUsOvG1dsJjSdOnn+2r1 Is303tpdz4IpptM0tvuEap90sdlyonkA/HVmgrtpHT9Fca3VUUsVUzmhjjlXODTVrJcdL1In /vKfstq1XqXSa3Wep8Jt9rRMI+RPERfMh21k1rpGjtMdLV6RoqiduEdK5eqgdJ4Y/wDLUnzy hauVEwt7kX/3lNo9P2if7E0HT3e8en/RKdPSTQLn3e4DTapzKuSGKpuiysz15pFXBdnhQ3H0 FRWuDR1ul8GqXNR73yPTlc/GOhVhuvdENei+kqgcnl6moXPULF1VBdtO0jLYrHpyMidhM5A9 Yblb6a62yWhro2zQTN5XtVOioU04nuHWyWC3SamsUjYGS1DWPjcvlcvkLI8P2pKy97YWutvt TCle9uHIsqKvTuOg4ucP2sRzFa9PDIvL7oGl8NXD1p6y0VJqa6IlXWrh8aouWovvFmGMaxqN Y1GtToiIncadtFLFDt/b1lljYnJ5XInkNT3i3v0/pCmfbbdURVt7m8SGDm6ZXpnIGqcXusaX wGj0RTXKnpqq5S9jO6R3SNq+VfcP34brZora3Tc9DU63tlVPO5HPVKjxU946DQuzcGrnP1fu PdIJblWdWU8krVSNvkx1Ns9Qbbtc/ddJ7v2xP3gSZ6ouhv7U2v55D85dwdATJyS6ltEieZ0q KRumxO3fkrKTp/eJ+8wmw+3PskrKT3+0T94G53K97TXBOWpudgcvny3J0lVSbJ1DFZJcrJ18 z2odR6g+3ec+GUmfhE/eE2H27cuUrKRcf3ifvA3Owag2qsdElHQXmxxx5z7NuTsF1xtynffr J8tpHnqDbdL1WrpPnE/eF2G26Xvq6Tp/eJ+8Df6vWG2tVSyU818sbo5Gq1ycze5SgnE7pzTl i3Akr9PXOkrLfWvVWsgdnkQt6mw+3ap0rKTHwifvPzfsFtnM3E01DIje7me3p/qBQJtPQP5X +ExImO7J9PpbeuVSqhRffL8Jw97Vr3eh/wAtoTh72qVcJ6H/AC2gUHWloHImaqHOPOYbSW9E 61UOffL8pw9bV5xi3/LaPW97V4z/AAf8tv7wPP64U9CymVzKiNzvMinUujwzm50x5D0XTh72 rVcJ6H/LafM/D1tfJTyQJJQNVyYaqPb4q+fvAgzhg4iaTR2nZbJqds1RE1USBWr7FqeQmn12 egv6rVfKQji68HtqluE0tHq2NsDnZY1HN6IcP1oFvyv+1jflNAlP12eg/wCq1XykNT3b4mtJ X/QlytFtgqGT1MLo0Vzk8qGsJwgW/p/tY35TR60C3qq41Yzr3JzNAqInjPXK4yvepyKaFiVS MmejU78qXk0Bwr6Nsavkvt7pq9zl8Vsj24Q293D7tc9eZ7re7zeO0Cgvglu/rUXxmXUtvd/x UPxl+PW9bV9elv6fnt/eY9b3tV//AK/5bQKEJT0Scv3XD090+X0lAucVUOffL9Lw87Wd2Lf8 tv7zDeHratEXK29f87f3gUH8FoFjRq1UOU90ytLb1RM1UOUTzl+E4e9qlXCeh/y2j1ve1Wcf wf8ALaBQdKagVnK6ri+M+EpKHK5q4ce+X7Xh62rTvS3/AC2/vCcPe1arhPQ/5bf3gUG8FoOz 5Vqoc++ZSnokVPuqHCJ5y/Hretq+vS39Pz2/vMJw9bVp3rb1z3eO394FBm01Aq8yVMSdfKpl 9Jb1yqVUOffL8+t62rzjFvz+m0Lw97VIuP4P+W0CgyUtvRP5VF8Z01TEzwiTs5Gq1F6YPRJO HratUzi34/Tb+8z633a1rei29ufz2gUf2N13WaD11SXOCVyU7ntbUIi97M9T1A0VqS36q07S 3q2yI6CoYjkTOVQpBxdbPWPR9pp79pqWnWnkekbo4np8ZvvAVuGtTQTaUrF6xYbBlQLeA+Wu znmwi5859AAAAAAAAAVy3hVE4jdO5X/hl+ksVTfyeP8AQT6Cue8v/qN04mMqtMv0li6b+Tx/ oJ9AH6AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAca6VXgdvmquRX9m3mwnepyT5kY2Rise iOa5MKigRRpDfrRt7vdVZ6ub0LqaeVY18JcjUcqeYk2GtiqqJ9VQzR1Eatyx0a5RSKtz+H/R 2rmyVNJSx225OXm8JjRc5Iddat69natZaCSq1FZYVzyPdhEaBsGsd1d5qHU9ZSWvTz5aOOVW xO8GVcoQLqTWm4VRvdFeqqhmZekczlp0jVE6d3ilptr+JDS2o5226/NbaLoqo1YXNXv99SN9 bSR1HGDSTwSRvjc6JUc1UVFAmbh71drjVFHXyaytrqKSKRGxIsXJlCWRhE8gAHHrubwWbuxy Lg5B+dUxZKeRje9zcIBWLh6VU301g1VTrWdULBai0hp7UFHLTXO10kqPyiv7JOb4yr+p9mN0 6XcS637Sl0qaFlZPz5j8qFj9orZqK1aRjpdT1slZcEdl0j+9QIc1pwuW10slbo251dtq3LzI nbq1mfeQ05ty332qqUgqWJerezoqxRq92PfLiHzLHHIxWSMa5q9FRUyBEexm9FNuDNUWye1V lBcKTCSpM3lRV9wl46S2aU0/bbnNcqG2wwVUy5kkamFcd2AAAAAAAAAAAA4d7uNNarXUV9VI 2OKFiuVyr07jlq5ExnylWeObdJLNYE0la6n7orG/bXNXqzC9wFYuI3cGfX+4lTVukctJC5Ym sRenRcZI8pW1UVUlRbY5kcxej296HGjevjvdl7396r5/OWe4IF0ZeK2t07qS0U1RVzORIHSd 6gQVLrTW8MTUfc7hG1OiZkch+S681iqInoxXdP75x6YVOzu3FSxGTaXontTyK043qIbX/wBk qH4lA85YtzdbxxoxLtVqieeRTDt09a5XN4qUX4Rf3nozLsbte9itTSlE1V8qIdc/h+2w6Iun KXmXy47wKB0O7mu6NMx3eV2fxnqp+VVdNSbi1HZ3OtiXwZeZZHr+0utuxtVtRozRdbeaqxUk atjVsaqn4WFwUJoryylv0lRC3sqSSVe0hTuVqKBPW220t03DpYqO2UraKnpcNlqJWY51TytU kyo4RYKtGrW3aadzU/DmVcGuaO4sbPprT9LaqHS8DGwsRrnNfjmVPKdv68+k6/7ORde/7YoH 7es5tf8AXP8A7B6zi1/1z/7D8fXn0idfS5F0/vFMrxoUq9+nI/nFA/X1nNr/AK5/9hn1nFr/ AK4vyz8PXn0nX/ZyLr/eKZ9ehS4x6XY8fCKB+vrObX/XP/sHrOLX/XP/ALD8fXn0n9nIun94 plONClTomnI0/wDcUD9fWc2v+ud394PWcWv+uf8A2H4+vPpOv+zkXXv+2KZ9efSZz6XIs/CK By2cIcEcToIrtMyF/s40mVGu99D8fWcWv+uf/Yfl69ClVcrpyPPwij16FLnPpcjz8IoH6+s5 teceGdfhB6zi1/1z/wCw/H151Hnm9LkWfP2imfXoUmc+lyPPwigfqvBza076z/7Dj3Tg/t9N bKiohrcSxRue3MnmTJ9Lxn0jvZaciX/3FPxruMikqaCppvS9G1ZYnMRe0XplMAV0p7jqLRt+ qaae43B0dK7Eaxyu5OinL1VvTrPUFnbYqmpbLSpIjmeVcp3HN9UyxVWnL9QXCwwzVVdGqU87 l6xKq96EVWyVlPVdo9MoidAJQ9V3VTrdHZLtXSR0kad0Dla7BxdrtGXPcXcmK2LV1EbJsvil qHrnl9xTRKSuhW/w1lbGk8LXor2L3OTzEy2Hemy2LXFnvls0/DDDb6ZYXRNXo9fOBO6cLVYj WtTVNyTCJ08McE4Wqzyapuf/AFbjpvXnUfRfS3Fn9NTKcZ9Imcaci6/3igdunC1V9capuX/W OM+tarMZ9NNyx/i3HTJxnUaZxpuLr+eo9efSYx6XIsfCKB3PrWqzv9NNy/6xw9a1WJ/+03JP /wDMcdMnGdRomPS5Fj4RQvGfSO9lpyJf/cUDufWtVn9qbl/1bh61qszj003LP+LcdOvGfSL3 6ci6f3imPXnUec+lyLPn7RQO5TharPJqm5/9W4wnC1V4XGqbl/1bjqE4z6ROiaci+cUwnGdR oiomm4uv56gdz61qsT/9puX/AFbjHrWqvOPTTcs/4tx0/rz6TGF05Fj4RR686jzn0uRZ8/aK B3PrWqzP9Kbl/wBW4x61qsX/APabl0/5tx1Hrz6TOfS5Fn4RTCcZ1Gmcabi6/nqB3PrWqxOv ppuX/VuDeFqrzldU3PH+LcdMvGfSKmF05Fj4RQnGfSImE05Fj4RQIs4gNtNXba3Ol8E1Hcqq nmbzcjKlyuxnqavR6105HAxlXXahSVERHp4S7v8AL5Te9w+I236r1XbrrU2CJ1PSxLG6BXZR 2SDty73bNQapmuVotsdupntTELO5F8qgbvT640890qy19/7Nq+Jipd3HT6j1HNc6iKLS9wvj EVURzpKhyon+poCuYkHKnslJD0ZriyWLRL7bJZIZ7i9zvuhV8ZEXuAsPt1w53a/6OoLxXaqu Pa1UaPREq3dDYPWs1n9qbl/1bjS9CcWlLp/R9us0lhjmdSx8ivV/ed4vGfSL36ci+cUDuPWt Vmcemm5Z/wAW4Jws1nk1Tcv+rcdN686jzn0uRZ8/aKZTjPpE6JpyL5xQO4TharF7tVXJf/8A McY9a1WY/pTcsf4xx07eM+kb7HTkSe9Io9edR4x6XIsfCKB3PrWqzGfTTcv+rcYXhaq/7U3L /q3HT+vPpMY9LkWPhFC8Z1GvfpuLp+eoHcrwtVnl1Tc/+rcPWtVn9qbl/wBW46f16FKvfpyP p/eKY9efSf2ci+cUDufWtVn9qbl/1bh61qs/tTcv+rcdN68+k6/7ORdf7xR68+k/s5F84oHc +tarP7U3L/q3D1rNZ/am5f8AVuOm9efSf2ci+cUevPpOv+zkXX+8UDufWtVnd6abl/1bh61q s/tTcv8Aq3HTevPpP7ORfOKPXn0n9nIund9sUDod6+HC7WTRMtzpb3WVvg+XyRyzue3Ce4Vx 2311edBXn0Rs7mNqGr+EmULL6v4uqS9aYrrUmnom+ExOj9n3ZKzarudjuFtpfAKCOmqWovbO b3uXIEsUfFduHHWxSTS07o0eivRGdVQuRsLu1aNydOxzwytZXsanbRqqIufePLqNWJHhyZcT 9wPVlRT7qwU0M72xSv8AHanc4D0UBhqqucpjr0Pl8sTFw+VjV91yIB9g/Lwmn9vi+Wg8Jp/b 4vloB+oPy8Jp/b4vloPCaf2+L5aAV33hVE4jdOqq/wDCr9JYimanYxu87E+grpvIrV4i9Nqj 43NWlVc86ecsRT1FOlPGnbxewT8NPMByAfDJonrhkrHL5kcin2AAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAA+J4Yp41jmjbIxe9rkyikF7wcQlv0rd1sdgovRi5J0dGxV6L5jVtO8TF4pr vTU2rtKSWulqXo1J3OVUb7oEk7mbD6L1mrqh1Mtvq0TLJKVEYuffQinbzh11PprdWG/VVz8M oYZGuY6SRXPwnum07ncRVNR1VNaND0Ho7XVUfOnZrjlNKpt+NztOVba3VOj52W5y+O9zujE8 4FuQa1tzrO0a207Dd7TO2Rr2osjU/AVfIbKAAPidHrA9I1w/HT3wPsFadS716y2/1xWUmqNO zSWR0v2mrVeiN8/QlbSu6mltW6eqrjp+6RTzRQK9Ys4VFRPdA+90N19K6AhR13qUkmX/AHMT kV/xEa2niw0XV1rYZ7Xc6aN7uVssjMNT3cmmbO6LpN1N1dSX7VzfDIKOdOxgevRMk7XvZvb6 5Wqa3OsNMznjVrHInVi46KBuGmb9bNQ2uO4WqqjqIZEyisci4O0KpcNE9bonePUm3jqx9TQ0 0rWQIq9GoWtAAAAAAABhXNTvVE99QMgxzs/Hb8Z89oiI5XK1Eb1znyAa/uRqel0lpGuvNTIx iwROdGjvwnJ5Dy53L1TW641jW3mpe9y1E32pqr3ZXyFhuOfdR1xubdG2ufEMDkfI9i+yz3oR jwq7bya81/TuqY1fbKV/21yp0z3oBJWiuHZlbsRUXytiey8NY6Zjcd7cZQr3oq9V+htcU9xY 58VTRy4e3u8p6w0lvpqe1x25sbVp2RpHy46KiJg8+OM7bWTSmun3ykplSiuD1kw1OjQL1baa qo9V6OobvRv7RHxtSRU64djqbOUk4ENzn0VbJou5z8tM5FkiVy/hL3IXbRcplAAXHf5ga5uV qWDSejLhfJ3IiU8SuRFXvAqPx77i+FXCHRtDKroURJJFavlQhzhv2r9UzU8tLI16UdPhZXJ5 lNM11fKzVms624STOlfU1CpCnuKvRC/fBxt+3Se3ENwmh7Kvrmfbcp1x5ANTfweaR/BnqPlj 1nmkPb6j5ZaJuUTCrkAVd9Z7o/yz1Hyx6zzR/t9R8stC5qOTCpkyBVxvB5pHrzTz+545lOD3 R6909R8stEYa1GphEAq6vB5pHmTE9Rj9Mz6z3R+cdvUfLLRGOVObmx1Aq67g80jjpPUZ/TM+ s90fjrPUfLLRGHNR3emQKves80h7fUfLMN4PNI48aeo+WWjAFXfWeaP9vqPlj1nujv6xUfLL RHz2bcYx5cgVeTg80jzLmefHk8cz6zzR/t9R8stEAKuO4PdI5TE8/wAsP4PNI48WefP6ZaJW oqoqp3GQKtpweaS5Os8/N+mfTeDzSGOs9Rn9MtEAKu+s90dnHhFRn4Qw3g80jlczz+545aFY 2q7mVOp9AVd9Z5o/2+o+WPWeaP8Ab6j5ZaIAVdXg90h1RJ6jP6ZhvB5pHHjT1Gf0y0XKnNzY 6mQKu+s80f7fUfLHrPdH/wBYqPllolTKYPlGNTHTu7gKvN4PNI9eaeo+WZ9Z5o/2+o+WWiAF XfWeaP8Ab6j5Y9Z7o/2+o+WWiMK1FVFVO4Crq8HukFTxaifP6Zn1nmkPb6j5ZaFrUbnCd5kC rvrPNH+31Hyx6z3R/t9R8stEFRFTC9wFXPWeaRVyYnn5f0zHrPdI8yolRP3dPHLSIiImE7jC NRHc2OoFXPWeaS5P4+fm/TC8HukVROWon93xy0hhrUamEAq96zzR/t9R8ses80f7fUfLLRBU ymFAq6nB7o9e6eo+WY9Z5pHm/j58fplomojUwncZAq76zzR/t9R8ses90f7fUfLLRGFa1Vzj r3AVdXg80iqpyzz4/TM+s80f7fUfLLQtRGphO4yBV31nuj/b6j5Y9Z5o/wBvqPllolRFTC9w RERMIBVxODzSPMuZ58eTxzPrPdH+31Hyy0RhrUbnCd4FXXcHmkemJ6j5Zn1nuj+7t6j5ZaIx ypzc2OoFXl4PNIY6T1Gf0zCcHukEb409R8stGYc1HJheqAVe9Z5o/wBvqPlmE4PNIpnmnnx5 PHLRp0TBhyI5ML1QCrnrPNJ4/j585/HJE2c2D0tt1cX3Gg7WSqcqKivdnBMCJhMADDmo7GfI pE27u1Vw1ndYaylvVZRJGuVbFOrEUloAVwXh6vWFT01XL/q3GW8PV4a3pqq558v3W4sa5qOT CoFRFTC9wFcPW8XpevpquX/VuMpw83jCKmqrnn/FuLHoiImPIYRGsauOiIBSjWm0jKDde02W q1LVyVU8Cua91Squb7mSSU4fLwrUVuqrlhWp/wAU4gjfDXqO4jaashkVPAajwdyov5xfTTdX FcbHSVbMKkkLM/EBGO020tw0dfkuNTfK2tZhfElnV6fETAERETCdwAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAHT61qpqLS9fU0/8bHEqtO4PyqqeKqp3087EfG9MORfKgFXeEPTdqvd71Lq O8RRVlwbcHtakqI7lT9ZOW5eiLRqLR9xtyWuk7aSFUhekaczV86eYr3f9J7hbP7i1F90lTz3 KxV86yTQRphGq5Sz+iLtU3vTdNcayldSzSN8aJ3eigQXwlbTv0wl5qdR0bJqyOrVtI+RuVSP 3Mk5assNpu2n6uirqOB8MkSovMxFwd2iInciJ7xX7iJ3K1fQXGo0ZpXT9RUVFQxGNqmL3KoG v8Hkktt1nrGxUr3PoIbgrY08jUTyIWiIb4Xdua/RWm6quvb1kut0kSefmTq13lQmQAAAOsv1 gtF8pXU91t9PVMcmPtjEdj4yvm4/DQ1JJbpoK51NurH5V0CScka+5hCwOo9RWfT1GtXeK6Kk hRMq56mrWjeHbu8VraK36lppJ1dhGecCp2hLtuLsVq+rde7XPXUVc/NQ+CNXomPMSpfOKa3z WmWCzWK6OucjFSNFgXCO8hY2uorfdaFWVFPFUwvTzIuTpKDb/SdHWJWU9ngZMnXOAIV4U9Fa hqL5dNw9WQdlV3RyPjYqYc330UsmdBa9V6eq7/V6eo62Ja+jVGzQNTCtO/AAAAAANX3L1taN Dacnu92mRrGNVWtz1cqeYo7uJxQ611FeZEsUbYaJiqkSMaqOVPdwS19kNhqfSxapEnckSyr4 qFLbTd3W+nc2CPEquyjwJYp98N1mJ27I6lzG9VXldg+JeJLcVzZIXzRorkVqplcocen3cji0 NHpyKyI+vcqo+pTGXIvkwRbdUmSsWWeJYHv6rnygftNU1+pNQI6pm56qrk5eeRe5VU9FeGPS 2n9B7fUyOuFA2vq40fOvaJ3lV+FHZOXcCslu9wVYKCJMxSK3orkUtCmwTm4a2/ORiJhGoi9A Ji9HLM5uPRSk/VKhHHEDprT+vtv6y2JcaN1WyNVhd2qZTBq9Tw+XJ71WDVj4m+blU/OLh6vD Hq5NYvXPRfEUCiFpranR+t2TwSuSSgqsOVq+yRq/9j032j13Q6u0HbrwlbTtmkjRZGq9MoUa 4o9nKrbu5tuLaxaqlqFRFkRuE5lOj2Cv1f6Z4NPTakW00VQ7lWR3VGgemLblRK5Pu2nVP00K kceO5MaUVPpW01bJFky2qRjsnf6w2w1Fp3TVVqGXc1G0rYlkhVWdH9MoiFI9S3Gtut7qK6ur HVUz347RfwuuAN74adESa33KoqR8T1hp1SVzkTp4q9x6fW6mio6KGmhYjGRsRqIieZCunA/t 56XtGrfa2LFXVLzRqqdeVULJAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAH51MqQ08kzu5jVVTTtvdwbdq6+3m1UbHtltb0bIrk6 Lk2q7Kq26qbjp2S9SBeFtqt3I19lP9+z6QLCgAAAAB0G4d19BdF3S583KsECuQ784GoLRRXy 1T224RdrTzN5Xt86AeTGsblJcNbXG8ZVyyVayp8eT0c4T9RLqHaC3VEr1WZuWuRe/CEIbnbU aLte99lslLbmMo6qBXyx59kuS0ugtH2TSNqjo7HSpTU6tReRPOBsgAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAD4nhimj7OZjXsXyOTKGYo44mIyJiManciJ0Po4Vwu1voJYoqyqjhfKv LGjl9koHNOJLbaCSqSqkpIXTp3SK3xvjOUxyPajmrlF7lMgAAAPiolbBA+Z/sWJlT7Pyq4Uq KWSBVwj2q3IFP7jarvvhvVcrTV3GoprDa51jc2J+OZPeN51Jwq6Xfa3LYblW0dwjbmKRruXL vJlTRrRfp9mN97ut/ge203epV7KlUw1EQtXpHUtl1ZaWXOy1jKqmVfZN84FZdBblau2hvrNJ 7ixSz25ruSKsRFd086uLR6evdtv1tiuFrq4qiCRqORWORce+dVuBoewa2s0ttvdGyZj2qiO7 lT9ZWOW2a+4fNSdtb1qLtpKSTmWNqLiNFXz+4gGybV8ycVmtmucq4nZ9BZ1reXPVVypUThs1 NTav3/1TqKhYrKeqkYqN83Qt2ioucLnAGQAAAAFWfshmfSZace3OKIcqtx5c9xe/7IWq+ky1 Jj/euKOU9FM1jKtWKsTXIqqBNmzWk7HY9G1G4erUarFYqUELk9nI3zovkI6ggrdwdxEgoaeN jqydHNiamEa3PVEQ+9Yayq75Y6O1tR0VvpF5mRovTPlLCcC+3VJUVs+s7sxka078QI9e9FAt ZtBpCj0ZoiitFLE1mI0c/CfhKnU28/KnmglZmGRjmp5lP0ynnQDIMZTzoZynnQCMeJHRFPrf bqto3xos1LG6eNcdconceZVTT1Nsr5aeTmhqqeTqvcqYU9f54454XwyIjmPTDk86HnhxRaHo tM7yeEVKsZbrnN3J3IB0euN6rnqbaal0bJNIjqd7VWTK5VqeTJpey+l5NX7iWuzciujmmRHr 5ENw3q2e9IOnKK9tu8VTBXMbJHA1MK1HdxKf2PzR7au8V9/qoc9hyugcqdwFz9MWyOzWCitk TWtbTQtj6J5kOxAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAOJdeb0Pqc+x7JSBuF7Pqk6+VV6LOzHxk9XVyehtSnlSNehAnC4u dytf9Mfb2fSBYUAAAAAAAFcd40ROI7TiOROtKv0liabm7GPu5eRMfEQ1uXoe9Xreiy6gpWOW ipYFY9UTpnJM8DVbCxq96NRAPsAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAK9cTU1RHr /RTIqmWJrq/DmtXo73ywpXbiccqbgaLREz93AWAtX83QZX8BDknFtGfQynz+IhygAAAAADXN aaK07q2jWnvVtgqF/Be9iKrfePvQmkbXo+0rbLUzkg5ubGMGwEQ8R+tb/pCLT7rHUJCtZcWQ TZbnLFXqBLxxLvbaK60ElFX08dRBIio5j0yh9WuV81vhlkXL3MRVU5IGgaC2n0zoy91l0s0X ZPqnZcxGojU9439ERO5AAAAAAHEu9fBbLbPXVDkSOFivd+oCrH2Q6ua3TNqpla7PbLhcdCq+ jqWt1Jan2WkpW8iJzvmVMYRPJk37in3fl3M1Cyz2uB3gdLKqRNTqrndx+C0Nw202mlbV4ir7 tyywtVvjIxe8CNdRU1kjpFSmqJPCGKrXM8mUPizaz1ZbKDwW23aup4U7mRPVEMaK0/PqrVlB a4GOc+sqEa/3Mr3noJprh422t2m6SC5WtjqtkSJNIsne4CiVJunr2lhViahubV+FU/T1X9fL GjU1Jcef4ZS69/2o2GtzXPungsCInXmlwQ/r6p4btPsf6GWb0SqG9GrFN5QIIk3a3DRUVdRX NrfKqyqdhRb4a9hi7P0brJEb+Esq5OLrish1A3OnNM1NFTquGqqZ6Ek7NWfbW26fVNZ2CWtr ZUTOHq3lUCPa7e/cCeRrm3usjRvmlXqcCjr79uZrChpb5c3uRX9JJpOjf1qWEqU4e4ERazSc sEa/hOmwhHW5LdE6p/g/bPTFVTMpP4+tZJlrfdA/Diov0lzvtl03SVCTQUtFHCnK7KK5OhcD hK0rHpzaW2vfHyVVRHmTKdVKBbfWetv+5dttskjpXwVLGvVevRHHqdYbfFb7RS0caIjYo0RM e8BzwAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAcS6q30Pqkx17JepAvC4udytfr/fs+knq7L/B1U3l6dkvUgXhcVV3I1+mMIk7 PpAsKAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAADDnNanM5yNRPKqlc+Jmo gdr/AESsdTC5q1/VUei4J01tS1FXpe4RUsvZTdg9WO91EU8uteah1VFqSWmuVwfJNQzudEqq vTqB6pWaWGS3QpFNHLhiIqtcinMIH4MEvcm3Utffap0755GuiVyr0aqE8AAAAAAH51E0cELp ZFwxvepWviz1VYa2DTTKa4QyPhusayI16LyoiljbvTx1dtqKZ69HxuTp7ynlbvRaqmxbg3Oh mnqMds+RiPeq4yq4wB6eaIv9qvFqibbquOdY2IjuVyLjobCVp4DrDNb9D1F2qZZXrWI1zVe5 VwWWQAAAAAAGk70SOg26ujmuVVWJ30KbsaBv3NHSbZ3N7+5WKn+igUL4ZbdbK7dntrtCyWmp 6hXuR6ZT2SnK38u9duBuxPYrMztY6SR0NLEnsUb7hpe3+o2WCtvU2VSSVHJGqL3LlScuB/Rc mo9eVeta6FZI6eRzV5kymVAhq3aG3C01rWGhoqCpiuScrmSMavKme7qS5LpbiNuUTo5K6dje VXOd26p0QvYtDRLIki0lOr07nLGmfjI+3/1a3SGgqqemfE2unVIomInjKjugFNNs9q9cbk6h q7bdL3Vvp6dF7SRZMplFwqFjdv8AhV0ZYOznuD33Cbvc2ZqKmTdOG/SEmmdBxyVTOWtq5HTv cqdVR3U2jW24OltJUUs93utNC9iZSJz8OcBml0Jo6kiSnj07QNjY3oqxpgjvdvVO0mgrbJNX 2m1zVnL4kTGI7r7pCW8HFbcLw+WzaHpZYHPXs+dfG5/eIdTb3Wl8utHc9VNqoobg7n5ps4wB xN39zYtdV6rT2GitlJG7xG06Y5kTuyh2Gmt0arTWg6uxU9hoYI69nKtU3+M984e7Oi7fpDcq 12Wj6QTxxPflc55u81/dK209rvi01JUMkiXHitX2IExcDGnHXvc+ou9THzwMjc5HKn4WT0Ca mERPMVr4DtMNte3Ul0majZpZlwqp1wpZQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAADi3b+bKn4NSBeF1f/EnX6eadnX9ZPF2 enofVMx3RKpA3C4ieqRr5UXvnZ9IFhQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAA6fVeo7Zpq2vr7pO2GFqZVzlwB2s8bZYXxO7ntVq/rPN7id0ZJRb8z0EDFSGrkajMJ3q XSbvnt+5yO9F6fu7+0Qg7eTUmgtS7oadvsVfA+OmqkfUqj+9oFktm7JFZNuLPRNbhUpmc/Ty m4p7hFcG9u3lNTMghu1OkbE5Wp2idEPpN9NAM8VLvT48/aIBKQIu9XbQOFX0Xp/nEMernoBH qvovT5x7YgEpAi5N9tBK1V9Fqfp/eIfK76aAa/m9FqdVx7YgEpOai96eTBQvja0dy7tUVRTx qkdbyRZx+EpaX1ddA8ufRen97tEIw3o1htzrWus0y3GnV9FVsmc7n8iKBM+xlhZp/a+z2xYk a+OBEf071N47kIqpt8NvaaFkEd1p2sY1ET7Yh+ib6aBc1f4Xp/nEAlEEWpvroFrExdqfHwiG Wb56ARcJd6fr1/jEAlEZTzkXN3y0Bzu/henz8Ih8+rlt/hU9FqfqvtgEpkacSz2M2ouKyd2P 2Kbzpq9UF/tMVzt0zZqeT2LmrlCPuKShra/aS4QUEL5pcovK1MrjqB5l01HJW3R1NCuJJZVb GnnXJ6acNOlKbSG2NBGvZRTVUTZZuqJl2DzTjorzR3HtoqOZssMqq3xe5ckjv3o3VZbIaJZ3 sggZyMxHjCAeldbdrZRwulqa+mjY1MrmRCne9+7+lbnvBb219R2tptzXNkYiczXuTuUrTqDW utL2q+HV9Yue9GvVDXGw1TpFkmhlkcq97uqqBZ3XPE7qrUMjbNo+2vihREjilhRc47kOo0zs huruZXJX6pqahtE52VdI/qiL7ikb7fbiXfRsnaWy2xOfjossKON8dxW7jQ/aldTwonc1sWAL R7U8OWi9GRslqaeO6VKIio6dieKp1vFB2dvWwMiYkVPH0RjU6J1K1+ux3FyipUw/IOk3E4gd R6ygokr+XtKbyo3GeoHZ8ZjkptzbRURN5VS2wvTHvEQ2uCp1RqyCmVznS1EiJ51Ox3R11X67 vVNcrljngp2wJhMdGkl8GOil1HubTXSWnc+koZEVy46AX02rsFLYNCWuggYjcU7Ff073YNpP mJjY42xsTDWphE8x9AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAcW7InobUrj/dqQLwupjcnX6p3LOzHxk83Xm9DqlfweyXoQ NwvJ/wCJOvlz3zs6frAsIAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAHW6gsN pv8AROorxQxVlO5MKyRMop2QA0H1GttM9NJW9OndyGW7ObbNTCaUoPkd5voA0H1GttcKnpTo Oq/imU2b20yq+lK3rnycim+gDQfUa20wqelOg6/mn0uzm2uMelK3fIU3wAaCmze2qKn+ydv6 fmmfUb21yq+lO39fzTfQBoKbN7apj/ZO39PzT6bs7ts1yuTSdv6+TkN8AGhJs3tplc6St658 7FDtm9tVTHpSt6e8xTfQBoS7N7aqqL6Urf0/MUJs3tqiKnpSt65/NU30AaF6je2vJy+lO3+/ y9THqNbacyL6Urf0/NN+AHBsdot1ktzLfaqSOlpY/YxsTCIcqpgiqYXQzxtkjcmHNVOiofof E0scLOeV7WN7sqoGqv220O96vdpyhVzlyq8h+c21+g5Y1Y/TVDhfzDcGOa9vM1UVPOhkDRfU h27/ALMUPyDKbRbdo1U9K9B18vIbyANFbtFt2jkX0r0PT8w41VsptnUyrJNpOgcv6BIYAjh2 x22Cpj0p0HueIfjV7EbZTw8iaXomL+MjCTQBEKcPG26NVPQKlXPl5DdtBaC03ounfFYrdDS9 p7NWNxk2gAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAABxLq5PQ6panf2akC8LmfVK1/n29n0k9XZyeh9SmO6JepAvC513K1 +uOizs+kCwoAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAARJxW3S42nbBKq11L6efw2FvO3vwq9UJbIZ4wkRdpkyuPu+H6QJC2zqJqrRlBPUSL JI6NFc5fL0NkNW2p/oNb/g0+hDaQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAADiXZV9DqlMdOyXqQLwuKq7k 6/RfJOz6Se7t/NlT8GpAvC6v/iTr9PIk7PpAsIAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEMcYiIu0qIq4+74fpJnIY4xOX1JU5u7w+H6QN 92s5m6GtyYz9rT6DajVtrW50PbsqvSNPoNpAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAB+FwqG0lBUVT/Ywxuev6kVQPyutxo7dAtRW1TII29VVyoh11n1fp67VHYUNyhlk83MhVSJ uouILc24UkdzmodP252V7GRWK7rhUO53N4e6vS1iW/aJvlyWto8Pc2SdcKidVAteioqZRcmH Oa1qucqIid6qpEHC5uLVa50Q30UVvojSuWOXH5vQ1bix3FvVrq6DQ+nF5K26J/GJ0VEzheoE z1mtdNU1WtHNdYWTd2OZDvKKohqadksEzZWOTKOauclarBww01Zp5lTeNQ3RbpOxJFc2oXCK qZOj2lv+p9r94I9v79WSVdsrHr4NJI5XORqe6oFt1VETKmv3fWmm7VVLTV10hilRcK3myR3x P69uultIQ0mn4HyV1yf2DHI3PLzJ0U0DbnhzbftOR3nWN8ui3KqbzuaydcNVQLL2q50N0pkq KGpjmjXuVrsnMKX1cOpdhN1aCmhuVRW2GvlZEiTSK7HMpcmgqY6ujiqYlyyRqOQD9wAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAcO7P+4KpmO6JVIG4XEb6pGvlRe+dnT9ZPd2wlsq Vx/u1IF4XUxuTr9fPOz6QLCAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAABDHGIiLtKiKuPu+H6xM5C/GOirtC5rfZLWwo338gb7tgqRaFtyvk axEjRVyvuH6X3X+krIjluV4p4OXvy4rPedv95rpoyjfYbrHHArEXDZlRcYK8bgaE3StFQ9Ly 25ViqvjOZzPQC92nt+NG6g1Y2w2atiqnucjUe1SWMp50PLHZC1arbr6nis9K6GvV6I3tmq1E XJcB9k4gkcqJJbfnFAsblPOgynnQretk4gl/3lt+cUytj4gsova235xQLHq5MLhUVffMNdlu Vwi++Vw9BOILOe0tvzimfQXiC9stvzigWPynnQZTzoVxSy8QXlktvzihLHxA8y8sttwv94oF jsp50MK7qmMKnvlcEsfEEmU7S2/OKZSycQSJjtLb84oFj8p50GU86FcPQXiC9stvzimfQTiB Vqosltz5PtigWO5k86DKedCuHoFxBKz+NtvT+8Uwtj4gvbLb84oFkMp50GU86FcfQTiCxntL b84p8pZOILOe0tvzigWQynnQZTzoVvSycQSZ+2W3r/eKfXoLxA8v8Zbc/CKBY1rsqucJju6m cp50K3usfEEv+9tvzimfQTiC9stvzigWPynnQZTzoVw9BeIL2y2/OKPQXiC9stvzigWPynnT 4zDHZRc4T9ZXFlk4gUcqrJbcfCKPQXiC8klt+cUCx+U86GGuznOE/WVyWy8QOOkltz5ftiny tj4glXPa275xQLIZTzoMp50K4tsvEDnrJbcfCKfvbrLv0lwgWqkt/g6SJz4kXOM9QLEHXamg dU6cuMDPZSUsjU99Wqcm2snZQxNqVRZkanNjznIVEVFRUyigVD4NrrRaY1pf9L3iZtNWK9Vj 7Tpz5cWH3e1TaNMaGuNZXVMTGyQuY1Fci5VUU0TePYK3atu66gs1XNbLqq5V0DuRFx7xWzeH b/UNs1baNGz6irLrV1ite6JZ1kajUXrlAJo4FbXOmn7he+VUp6qeTk83sjh8Xlmu1n1tY9fU VK6ppaBOWbzNypP+12maPSWjqGy0cfI1kbXO6Y8ZU6kI8WGs7hcrpQ7aWCGKaouSZkV6d2F6 gSXpfeTQNbpunuDr5Txq2FqSoq+xVE6oQZRVsu7HEfQ3iy06yWe0vcx1S3udnuU2HT/CRpl2 m2Mr7vc4quVnM9kcmGI5U7jV9uJbpsLuvHpCshjfZbtIqxzKmX4Tu6gWuuun7Vc206XCjZUr AqKxXeRU8p+t2uVrslB2lfPHTU7E73dERDn08rZ4I5mexe1HJ7ymqbn6Ct+vbG+03Gsq6WJy Y5qd2HAVv35vcO6O6Nk09pHluEFJURzTTx9zcL1LZWWjS32uno0dzdmxG5Ka3bTFx4ddxaC5 2pzayzV0rIHyVC8z+q9S5FkucF0tdNXU6qsc7Ec1QOcYc7CLjCr5sh6KrFRvfjoQZrq0bzy6 lqZNPyUPgCr9q53qi4AnNHJjqqfGMp50K4egvEF7ZbfnFMpZeIHPWS24+EUCx2U86DmTzoVw bY+ILKoktt+cUx6B8QXLjtLb84oFj+bxsdMefJnKedCuCWTiCRMdpbfnFHoLxBe2W35xQLH5 TzoMp50K4LZOIFWqiyW3PwihbHxBcqL2tt+cUCx+U86DKedCt/oJxBZz2lt+cU+vQTiCxntL b84oFjsp50HMnnQrelj4gkz9stvX+8UNsnEEn+8tvzigWQynnQwx2UXmwn6yuS2XiBx0ktuf L9sU+VsfEEq57W3fOKBZDKedBlPOhXD0F4gvbLb84o9BeIL2y2/OKBY/KedBzJjvT4yuHoLx Be2W35xQyycQKZzLbvnFAscx2W5XCL75nmTHenxlcPQXiC9stvzimVsvED5JLb84oFjWOynX CL75nKedCt62PiC5s9rbvnFM+gvEF7ZbfnFAsflPOgynnQrh6C8QXtlt+cUegvEF7ZbfnFAs erkwqoqL+sNdlMqqIvvlcGWTiBRFRZLd84plLJxBquO0tvzigShrbdvSOjtRss1/uMVJI9qK iuXznd2HXWlr41HWy7086L3YceenE/Q61i1oyPVzYn13I3Cwrnp5DTdK0W4T6trLIy8MRF6K xHI0D1Vub0dbalWq1W9kqoqKQNwuLncrX+fb2fSaFtRZd/W0Mj5ZoX0vZdUqZF5sfrN04RUq 26z1uy48vhiSs7Xl7sgWOAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAACGeMP70ydcfd8P0kzGp7qaJoteaY9A66aSGLtmS8zO/LVA+9quuhbf nr9rT6ENhqKKmqY3x1EEUjHeRWIcbTVqistmgtsLlcyFqNRV7zsQNWpdvtKUt4S7QWqKOsRc pInnNpAA+WNVEw5cqfQAAAABhAAAAADAADAAAYAAAYAAAAAAAGAAAwgAADCAAAAB0+s77Tab 0zXXqqciRUsSvXKlZ+GOx1Wu9zrxuTdkdJFDUOZRo/qnIvmJ+3Z0NFr3TjrJUVtRSwSZSRYl wrkOftzpC26K0vS2O2N+1QMRqvVOr8eVQNhVeXCI3Kd3vFRN+HT6H4hrFq+ugc63crkfIqdG 5Ut6a7r3Rtk1lZZLZeKWOVj0w16tRXN94DNj1jp252SO50tzp306xo5zub2PQq9vJfqXc7fn Ttq0zIlQy3q5s0rEyiLnJtdRwtxxTugt+r71BQvd40bZsIiL5MEpbS7SaY2/hd6HxrVVi+yq Zm+Pn3wNF4iNZ6v2+hsFXbJnx2xskcdVhvTlTvySpobXen9T6fp7nR3GF6SRo5yc3cdrqzTt r1NZ5rXdqaOeCRqp4zc8ufKhANy4XYaere6w6ru9FTvXPZRy8rW+4iAa7xg6otmrLtZNH2KZ tZXNrY3v7Prypkstt1bJ7Po23W+pz2sUSI7JoO1Gw2m9FV/opPPNdrgqfxtV4yovuKS8AAAA AAMIAAAAAYQYAADAAAAAMIAAAAADAAAYQAAAAAAAYQAAabqvbTSOp70l2vlsZV1DWojVVfMd 1YNNWSzQJHbrdDA3zcqKp3AA4d0Zy22p5URE7JeiIQNwuI5Nydfq7yzs+ksDVRJPTSQquEe1 Wml7c7dUGjr9ertSVEssl1ejpEevRuPMBvAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAD/9k=